Aberrant Brain Spontaneous Activity and Synchronization in Type 2 Diabetes Mellitus Patients: A Resting-State Functional MRI Study

Altered cerebellar activity and cognitive deficits in Type 2 diabetes: Insights from resting-state fMRI

OBJECTIVE

To investigate alterations in brain activity in patients with Type 2 Diabetes and explore the relationship between altered regions and neuropsychological performances.

METHODS

A total of 36 patients with Type 2 Diabetes and 40 age- and education-matched healthy controls were recruited for this case-control study. All participants underwent resting-state functional magnetic resonance imaging (Resting-state fMRI) and neuropsychological tests. The neuropsychological scales included the Auditory Verbal Learning Test (AVLT), Shape Trajectory Test B (STT-B), Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), and Boston Naming Test (BNT), Symbol Digit Modality Test (SDMT), Regional homogeneity (ReHo) and the amplitude of low-frequency fluctuations (ALFF) were used to assess differences in spontaneous regional brain activity. For functional connectivity (FC) analyses, the differences identified among the groups were selected as seed regions. Then, the correlations between neuropsychological scale scores (AVLT, HAMA, HAMD, STT-B, BNT, and SDMT) and ALFF/ReHo values were specifically analyzed in the focal regions that exhibited significant alterations between the T2DM and control groups, as detailed in Tables 2 and 3.

RESULTS

Patients with Type 2 Diabetes exhibited significantly higher ALFF values in the superior lobe of the cerebellum, specifically in the left cerebellar crus I (Cerebellum_Crus I_L), left cerebellar lobule VI (Cerebellum_6_L), and left cerebellar lobule IV-V (Cerebellum_4_5_L). Additionally, they exhibited elevated ReHo values in the Cerebellum_Crus I_L and Cerebellum_6_L. The findings were statistically significant with a family-wise error-corrected, cluster-level p-value of less than 0.05. However, the FC analysis was not significant. AVLT scores were significantly lower in the diabetes group. The correlation analysis demonstrated a negative association between ALFF values of the Cerebellum_6_L and AVLT scores (R2 = 0.1375, P < 0.001). The ReHo values within the Cerebellum_6_L also exhibited a negative association with AVLT scores (R2 = 0.0937, P = 0.007).

CONCLUSION

Patients with Type 2 Diabetes showed abnormal neural activities in diverse cerebellar regions mainly related to cognitive functions. This provides supplementary information to deepen our insight into the neural mechanisms by which Type 2 Diabetes affects the functional activity of the brain's posterior circulation, as well as the potential association of these changes with cognitive impairment.

Altered Interhemispheric Functional Connectivity in Patients With Diabetic Retinopathy: A Resting-State Functional MRI Study

OBJECTIVE

Cognitive impairment is a prevalent complication among patients with diabetes mellitus. It tends to be more prominent in patients with diabetic retinopathy (DR) compared with patients with diabetes without DR (NDR). However, the functional connectivity (FC) between bilateral cerebral hemispheres in both remains poorly understood. This study aimed to investigate altered brain connectivity in patients with DR and NDR.

SUBJECTS AND METHODS

We selected 26 patients with DR, 30 patients with NDR, and 30 healthy controls (HCs) to participate in resting-state functional magnetic resonance imaging (rs-fMRI) and high-resolution T1-weighted structural scans. We employed the DPABI toolbox in MATLAB to preprocess the acquired images and applied voxel-mirrored homotopic connectivity (VMHC) and FC analysis methods to estimate differences among the 3 groups. The patients also underwent neuropsychological assessment scales. We utilized partial correlation analysis to explore the associations between aberrant connections and clinical variables as well as neuropsychological characteristics in patients with DR. Receiver operating characteristic (ROC) analysis was conducted to assess the diagnostic performance of VMHC values in distinct brain regions for differentiating DR patients from NDR patients.

RESULTS

The results showed significantly altered VMHC values across the 3 groups, including bilateral lingual gyrus (LING_B), superior temporal gyrus (STG_B), and postcentral gyrus (PoCG_B). Significant differences in FC values were found across the LING_B, right cuneus (CUN_R), STG_R, PoCG_B, right precentral gyrus (PreCG_R), right precuneus (PCUN_R), and middle temporal gyrus (MTG_L) among the 3 groups. Moreover, a negative correlation was noted between the VMHC values of LING_B and disease duration in patients with DR. Positive correlations were detected between FC values in PoCG_B and fasting blood glucose (FBG) levels. Furthermore, ROC analysis of the VMHC values demonstrated that combining all the differential regions achieved the highest area under the curve of 0.826.

CONCLUSIONS

Significant alterations in VMHC and FC may reflect the underlying neuropathology of cognitive dysfunction in DR and NDR. These altered connectivity patterns could serve as neuroimaging biomarkers, offering insights into the early diagnosis and intervention of cognitive impairments in DR patients.

Support Vector Machine for Stratification of Cognitive Impairment Using 3D T1WI in Patients with Type 2 Diabetes Mellitus

Purpose

To explore the potential of MRI-based radiomics in predicting cognitive dysfunction in patients with diagnosed type 2 diabetes mellitus (T2DM).

Patients and Methods

In this study, data on 158 patients with T2DM were retrospectively collected between September 2019 and December 2020. The participants were categorized into a normal cognitive function (N) group (n=30), a mild cognitive impairment (MCI) group (n=90), and a dementia (DM) group (n=38) according to the Chinese version of the Montréal Cognitive Assessment Scale-B (MoCA-B). Radiomics features were extracted from the brain tissue except ventricles and sulci in the 3D T1WI images, support vector machine (SVM) model was then established to identify the CI and N groups, and the MCI and DM groups, respectively. The models were evaluated based on their area under the receiver operating characteristic curve (AUC), Precision (P), Recall rate (Recall, R), F1-score, and Support. Finally, ROC curves were plotted for each model.

Results

The study consisted of 68 cases in the N and CI group, with 54 cases in the training set and 14 in the verification set, and 128 cases were included in the MCI and DM groups, with 90 training sets and 38 verification sets. The consistency for inter-group and intra-group of radiomics features in two physicians were 0.86 and 0.90, respectively. After features selection, there were 11 optimal features to distinguish N and CI and 12 optimal features to MCI and DM. In the test set, the AUC for the SVM classifier was 0.857 and the accuracy was 0.830 in distinguishing CI and N, while AUC was 0.821 and the accuracy was 0.830 in distinguishing MCI and DM.

Conclusion

The SVM model based on MRI radiomics exhibits high efficacy in the diagnosis of cognitive dysfunction and evaluation of its severity among patients with T2DM.

Abnormal changes of brain function and structure in patients with T2DM-related cognitive impairment: a neuroimaging meta-analysis and an independent validation

Type 2 diabetes mellitus (T2DM) seriously threatens human health and the quality of life, cognitive impairment is considered as a common complication of T2DM. Neuroimaging meta-analysis found brain functional and structural abnormality in patients with T2DM. Therefore, the purpose of the meta-analysis was to identify brain regions of patients with T2DM-related cognitive impairment (T2DM-CI) where functional and structural indicators changed together or could not synchronize. A literature screening of neuroimaging studies on cognitive impairment in T2DM was conducted from 1 January 2007 to 26 May 2023 in PubMed, Web of Science, Cochrane Library, and Medline databases. The functional indicators we studied were amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and degree centrality (DC), while the structural indicator was gray matter (GM), which included gray matter volume (GMV) and cerebral cortical thickness. Studies reporting ALFF, ReHo, DC and GM abnormalities between T2DM-CI and healthy controls (HCs) were selected and their significant peak coordinates (x, y, z) and effect size (t-value) were extracted to perform a meta-analysis using anisotropic effect size sign differential mapping (AES-SDM) 5.15 software. Moreover, the brain regions with significant differences obtained from meta-analysis were saved as masks and then validated in our data. Total 19 studies and 20 datasets were involved in this study. Compared to HCs, combining ALFF, ReHo, and DC measurements, the brain activity of the left anterior cingulate/paracingulate gyri (ACC.L, BA24) in T2DM-CI patients increased significantly, while the brain activity of the left lingual gyrus (LING.L, BA18) in T2DM-CI patients decreased significantly. The GM indicator of the right superior temporal gyrus (STG.R, BA42) and left inferior occipital gyrus (IOG.L, BA19) in T2DM-CI patients decreased significantly. Meta-regression analysis showed the negative relationship between the brain activity reduction in LING.L and the percentage of female patients, as well as the negative relationship between GM reduction in IOG.L and T2DM duration. Furthermore, we validated a decrease in brain activity in the LING.L of T2DM-CI patients in our independent dataset. The decrease of brain activity in LING.L and the decrease of GM in IOG.L were closely related to visual impairment in T2DM-CI patients. These abnormal brain regions may be the main targets for future research, early intervention can delay the further development of cognitive impairment in T2DM patients and improve their quality of life, which also provided early biomarkers for clarifying the mechanism of cognitive impairment in T2DM.

The Interplay of Sports and Nutrition in Neurological Health and Recovery

This comprehensive review explores the dynamic relationship between sports, nutrition, and neurological health. Focusing on recent clinical advancements, it examines how physical activity and dietary practices influence the prevention, treatment, and rehabilitation of various neurological conditions. The review highlights the role of neuroimaging in understanding these interactions, discusses emerging technologies in neurotherapeutic interventions, and evaluates the efficacy of sports and nutritional strategies in enhancing neurological recovery. This synthesis of current knowledge aims to provide a deeper understanding of how lifestyle factors can be integrated into clinical practices to improve neurological outcomes.

Alterations of spontaneous brain activity in type 2 diabetes mellitus without mild cognitive impairment: a resting-state functional magnetic resonance study

Background

Type 2 diabetes mellitus (T2DM) has been demonstrated an increased risk factor of cognitive impairment or even dementia. Kinds of resting-state functional magnetic resonance imaging indices have been proposed and used to investigate the brain mechanism underlying diabetic cognitive impairment. This study aimed to explore the early changes in spontaneous neural activity among T2DM patients without cognitive impairment by means of multiple rs-fMRI indices.

Methods

T2DM patients without cognitive impairment and age-, sex-, and education matched control subjects were included in this study. Three rs-fMRI indices, namely amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and voxel-mirrored homotopic connectivity (VMHC) were computed after image pre-processing. The Montreal Cognitive Assessment (MoCA) was performed to distinguish normal cognition. Brain volume was also evaluated. Correlation analyses were conducted to explore any relationship among rs-fMRI indices and clinical characteristics.

Results

The T2DM patients were detected significantly decreased neural activity in right angular and left prefrontal gyrus including middle and superior frontal gyrus. Increased activities were also observed in left caudate and the supplementary motor area. No correlation between rs-fMRI indices and clinical characteristics was survived after multiple comparison correction. But we observed a significant, but decreased correlation between ALFF and ReHo values in the reported brain areas.

Conclusion

The combination of ALFF, ReHo and VMHC analyses demonstrated abnormal spontaneous neural activity in brain regions which were reported in T2DM patients without cognitive impairment. These results may enhance our understanding of the diabetic brain changes at the early stage.

The older adult brain is less modular, more integrated, and less efficient at rest: A systematic review of large-scale resting-state functional brain networks in aging

The literature on large-scale resting-state functional brain networks across the adult lifespan was systematically reviewed. Studies published between 1986 and July 2021 were retrieved from PubMed. After reviewing 2938 records, 144 studies were included. Results on 11 network measures were summarized and assessed for certainty of the evidence using a modified GRADE method. The evidence provides high certainty that older adults display reduced within-network and increased between-network functional connectivity. Older adults also show lower segregation, modularity, efficiency and hub function, and decreased lateralization and a posterior to anterior shift at rest. Higher-order functional networks reliably showed age differences, whereas primary sensory and motor networks showed more variable results. The inflection point for network changes is often the third or fourth decade of life. Age effects were found with moderate certainty for within- and between-network altered patterns and speed of dynamic connectivity. Research on within-subject bold variability and connectivity using glucose uptake provides low certainty of age differences but warrants further study. Taken together, these age-related changes may contribute to the cognitive decline often seen in older adults.

Aberrant brain functional networks in type 2 diabetes mellitus: A graph theoretical and support-vector machine approach

Objective

Type 2 diabetes mellitus (T2DM) is a high risk of cognitive decline and dementia, but the underlying mechanisms are not yet clearly understood. This study aimed to explore the functional connectivity (FC) and topological properties among whole brain networks and correlations with impaired cognition and distinguish T2DM from healthy controls (HC) to identify potential biomarkers for cognition abnormalities.

Methods

A total of 80 T2DM and 55 well-matched HC were recruited in this study. Subjects’ clinical data, neuropsychological tests and resting-state functional magnetic resonance imaging data were acquired. Whole-brain network FC were mapped, the topological characteristics were analyzed using a graph-theoretic approach, the FC and topological characteristics of the network were compared between T2DM and HC using a general linear model, and correlations between networks and clinical and cognitive characteristics were identified. The support vector machine (SVM) model was used to identify differences between T2DM and HC.

Results

In patients with T2DM, FC was higher in two core regions [precuneus/posterior cingulated cortex (PCC)_1 and later prefrontal cortex_1] in the default mode network and lower in bilateral superior parietal lobes (within dorsal attention network), and decreased between the right medial frontal cortex and left auditory cortex. The FC of the right frontal medial-left auditory cortex was positively correlated with the Montreal Cognitive Assessment scales and negatively correlated with the blood glucose levels. Long-range connectivity between bilateral auditory cortex was missing in the T2DM. The nodal degree centrality and efficiency of PCC were higher in T2DM than in HC (P < 0.005). The nodal degree centrality in the PCC in the SVM model was 97.56% accurate in distinguishing T2DM patients from HC, demonstrating the reliability of the prediction model.

Conclusion

Functional abnormalities in the auditory cortex in T2DM may be related to cognitive impairment, such as memory and attention, and nodal degree centrality in the PCC might serve as a potential neuroimaging biomarker to predict and identify T2DM.

Changes of brain function in patients with type 2 diabetes mellitus measured by different analysis methods: A new coordinate-based meta-analysis of neuroimaging

Objective

Neuroimaging meta-analysis identified abnormal neural activity alterations in patients with type 2 diabetes mellitus (T2DM), but there was no consistency or heterogeneity analysis between different brain imaging processing strategies. The aim of this meta-analysis was to determine consistent changes of regional brain functions in T2DM via the indicators obtained by using different post-processing methods.

Methods

Since the indicators obtained using varied post-processing methods reflect different neurophysiological and pathological characteristics, we further conducted a coordinate-based meta-analysis (CBMA) of the two categories of neuroimaging literature, which were grouped according to similar data processing methods: one group included regional homogeneity (ReHo), independent component analysis (ICA), and degree centrality (DC) studies, while the other group summarized the literature on amplitude of low-frequency fluctuation (ALFF) and cerebral blood flow (CBF).

Results

The final meta-analysis included 23 eligible trials with 27 data sets. Compared with the healthy control group, when neuroimaging studies were combined with ReHo, ICA, and DC measurements, the brain activity of the right Rolandic operculum, right supramarginal gyrus, and right superior temporal gyrus in T2DM patients decreased significantly. When neuroimaging studies were combined with ALFF and CBF measurements, there was no clear evidence of differences in the brain function between T2DM and HCs.

Conclusion

T2DM patients have a series of spontaneous abnormal brain activities, mainly involving brain regions related to learning, memory, and emotion, which provide early biomarkers for clarifying the mechanism of cognitive impairment and neuropsychiatric disorders in diabetes.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=247071, PROSPERO [CRD42021247071].

Differences in brain activity between normal and diabetic rats under isoflurane anesthesia: a resting-state functional MRI study

BACKGROUND

Altered neural activity based on the fractional amplitude of low-frequency fluctuations (fALFF) has been reported in patients with diabetes. However, whether fALFF can differentiate healthy controls from diabetic animals under anesthesia remains unclear. The study aimed to elucidate the changes in fALFF in a rat model of diabetes under isoflurane anesthesia.

METHODS

The first group of rats (n = 5) received a single intraperitoneal injection of 70 mg/kg streptozotocin (STZ) to cause the development of diabetes. The second group of rats (n = 7) received a single intraperitoneal injection of the same volume of solvent. Resting-state functional magnetic resonance imaging was used to assess brain activity at 4 weeks after STZ or solvent administration.

RESULTS

Compared to the healthy control animals, rats with diabetes showed significantly decreased fALFF in various brain regions, including the cingulate cortex, somatosensory cortex, insula, and striatum (all P < 0.05). The decreased fALFF suggests the aberrant neural activities in the diabetic rats. No regions were detected in which the control group had a lower fALFF than that in the diabetes group.

CONCLUSIONS

The results of this study demonstrated that the fALFF could be used to differentiate healthy controls from diabetic animals, providing meaningful information regarding the neurological pathophysiology of diabetes in animal models.

Impairments in intrinsic functional networks in type 2 diabetes: A meta-analysis of resting-state functional connectivity

Type 2 diabetes mellitus (T2DM) is associated with abnormal communication among large-scale brain networks, revealed by resting-state functional connectivity (rsFC), with inconsistent results between studies. We performed a meta-analysis of seed-based rsFC studies to identify consistent network connectivity alterations. Thirty-three datasets from 30 studies (1014 T2DM patients and 902 healthy controls [HC]) were included. Seed coordinates and between-group effects were extracted, and the seeds were divided into networks based on their location. Compared to HC, T2DM patients showed hyperconnectivity and hypoconnectivity within the DMN, DMN hypoconnectivity with the affective network (AN), ventral attention network (VAN) and frontal parietal network, and DMN hyperconnectivity with the VAN and visual network. T2DM patients also showed AN hypoconnectivity with the somatomotor network and hyperconnectivity with the VAN. T2DM illness durations negatively correlated with within-DMN rsFC. These DMN-centered impairments in large-scale brain networks in T2DM patients may help to explain the cognitive deficits associated with T2DM.

Optimized electroencephalogram and functional near-infrared spectroscopy-based mental workload detection method for practical applications

Background

Mental workload is a critical consideration in complex man–machine systems design. Among various mental workload detection techniques, multimodal detection techniques integrating electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals have attracted considerable attention. However, existing EEG–fNIRS-based mental workload detection methods have certain defects, such as complex signal acquisition channels and low detection accuracy, which restrict their practical application.

Methods

The signal acquisition configuration was optimized by analyzing the feature importance in mental workload recognition model and a more accurate and convenient EEG–fNIRS-based mental workload detection method was constructed. A classical Multi-Task Attribute Battery (MATB) task was conducted with 20 participating volunteers. Subjective scale data, 64-channel EEG data, and two-channel fNIRS data were collected.

Results

A higher number of EEG channels correspond to higher detection accuracy. However, there is no obvious improvement in accuracy once the number of EEG channels reaches 26, with a four-level mental workload detection accuracy of 76.25 ± 5.21%. Partial results of physiological analysis verify the results of previous studies, such as that the θ power of EEG and concentration of O₂Hb in the prefrontal region increase while the concentration of HHb decreases with task difficulty. It was further observed, for the first time, that the energy of each band of EEG signals was significantly different in the occipital lobe region, and the power of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta_{1}$$\end{document}β1 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta_{2}$$\end{document}β2 bands in the occipital region increased significantly with task difficulty. The changing range and the mean amplitude of O₂Hb in high-difficulty tasks were significantly higher compared with those in low-difficulty tasks.

Conclusions

The channel configuration of EEG–fNIRS-based mental workload detection was optimized to 26 EEG channels and two frontal fNIRS channels. A four-level mental workload detection accuracy of 76.25 ± 5.21% was obtained, which is higher than previously reported results. The proposed configuration can promote the application of mental workload detection technology in military, driving, and other complex human–computer interaction systems.

Aberrant Brain Spontaneous Activity and Synchronization in Type 2 Diabetes Mellitus Subjects Without Mild Cognitive Impairment

Objective: We aimed to explore whether the percent amplitude of fluctuation (PerAF) measurement could provide supplementary information for amplitude of low-frequency fluctuation (ALFF) about spontaneous activity alteration in type 2 diabetes mellitus (T2DM) subjects without mild cognitive impairment (MCI). Then we further evaluated the synchronization through the method of functional connectivity (FC) to better demonstrate brain changes in a more comprehensive manner in T2DM. Methods: Thirty T2DM subjects without MCI and thirty well-matched healthy subjects were recruited in this study. Subjects' clinical data, neuropsychological test results, and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired. Voxel-based group difference comparisons between PerAF and ALFF were conducted. Then, seed-based FC between the recognized brain regions based on PerAF and ALFF and the rest of the whole brain was performed. Results: Compared with healthy group, T2DM group had significantly decreased PerAF in the bilateral middle occipital gyrus and the right calcarine, increased ALFF in the right orbital inferior frontal gyrus and decreased ALFF in the right calcarine. Seed-based FC analysis showed that the right middle occipital gyrus of T2DM subjects exhibited significantly decreased FC with the right caudate nucleus and right putamen. According to the partial correlation analyses, hemoglobin A1c (HbA1c) and immediate memory scores on the auditory verbal learning test (AVLT) were negatively correlated in the T2DM group. However, we found that total cholesterol was positively correlated with symbol digit test (SDT) scores. Conclusion: PerAF and ALFF may have different sensitivities in detecting the abnormal spontaneous brain activity in T2DM subjects. We suggest PerAF values may add supplementary information and indicate additional potential neuronal spontaneous activity in T2DM subjects without MCI, which may provide new insights into the neuroimaging mechanisms underlying early diabetes-associated cognitive decline.

A multimodal meta-analysis of regional structural and functional brain alterations in type 2 diabetes

Neuroimaging studies have identified brain structural and functional alterations of type 2 diabetes mellitus (T2DM) patients; however, there is no systematic information on the relations between abnormalities in these two domains. We conducted a multimodal meta-analysis of voxel-based morphometry and regional resting-state functional MRI studies in T2DM, including fifteen structural datasets (693 patients and 684 controls) and sixteen functional datasets (378 patients and 358 controls). We found, in patients with T2DM compared to controls, conjoint decreased regional gray matter volume (GMV) and altered intrinsic activity mainly in the default mode network including bilateral superior temporal gyrus/Rolandic operculum, left middle and inferior temporal gyrus, and left supramarginal gyrus; decreased GMV alone in the limbic system; and functional abnormalities alone in the cerebellum, insula, and visual cortex. This meta-analysis identified complicated patterns of conjoint and dissociated brain alterations in T2DM patients, which may help provide new insight into the neuropathology of T2DM.

Regional Spontaneous Neural Activity Alterations in Type 2 Diabetes Mellitus: A Meta-Analysis of Resting-State Functional MRI Studies

Objective: Resting-state functional magnetic resonance imaging (rs-fMRI) studies have revealed inconsistent regional spontaneous neural activity alterations in patients with type 2 diabetes mellitus (T2DM). The aim of our meta-analysis was to identify concordant regional spontaneous neural activity abnormalities in patients with T2DM. Methods: A systematic search was conducted to identify voxel-based rs-fMRI studies comparing T2DM patients with healthy controls. The permutation of subject images seed-based d mapping (SDM) was used to quantitatively estimate the regional spontaneous neural activity abnormalities in patients with T2DM. Metaregression was conducted to examine the associations between clinical characteristics and functional alterations. Results: A total of 16 studies with 19 datasets including 434 patients with T2DM and 391 healthy controls were included. Patients with T2DM showed hypoactivity in the right medial superior frontal gyrus, right superior temporal gyrus, and left lingual gyrus, whereas hyperactivity in the right cerebellum. Metaregression analysis identified negative correlation between regional activity in the medial superior frontal and anterior cingulate gyri and illness duration of patients with T2DM. Conclusion: The patterns of regional spontaneous neural activity alterations, characterized by hypoactivity in the medial pre-frontal cortex, visual cortex, and superior temporal gyrus, whereas hyperactivity in the cerebellum, might represent the underlying neuropathological mechanisms of T2DM.