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Background and purpose Neurodegenerative processes are widespread in the brains of type 2 diabetes mellitus (T2DM) patients; gaps remain to exist in the current knowledge of the associated gray matter (GM) microstructural alterations. Methods A cross‐sectional study was conducted to investigate alterations in GM microarchitecture in T2DM patients by diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI). Seventy‐eight T2DM patients and seventy‐four age‐, sex‐, and education level‐matched healthy controls (HCs) without cognitive impairment were recruited. Cortical macrostructure and GM microstructure were assessed by surface‐based analysis and GM‐based spatial statistics (GBSS), respectively. Machine learning models were trained to evaluate the diagnostic values of cortical intracellular volume fraction (ICVF) for the classification of T2DM versus HCs. Results There were no differences in cortical thickness or area between the groups. GBSS analysis revealed similar GM microstructural patterns of significantly decreased fractional anisotropy, increased mean diffusivity and radial diffusivity in T2DM patients involving the frontal and parietal lobes, and significantly lower ICVF values were observed in nearly all brain regions of T2DM patients. A support vector machine model with a linear kernel was trained to realize the T2DM versus HC classification and exhibited the highest performance among the trained models, achieving an accuracy of 74% and an area under the curve of 83%. Conclusions NODDI may help to probe the widespread GM neuritic density loss in T2DM patients occurs before measurable macrostructural alterations. The cortical ICVF values may provide valuable diagnostic information regarding the early GM microstructural alterations in T2DM. Detecting early cortical microstructural alterations in type 2 diabetes mellitus (T2DM) patients without cognition decline with gray matter‐based spatial statistics. Significantly lower intracellular volume fractions (ICVF) values were observed in nearly whole brain regions of T2DM patients. A linear support vector machine model was trained with cortical ICVF to realize the T2DM versus HC classification and exhibited the highest performance among the trained models, achieving an accuracy of 74% and an area under the curve of 83%.

Major depressive disorder (MDD) exhibits notable sex differences in prevalence and clinical and neurobiological manifestations. Though the relationship between peripheral inflammation and MDD-related brain changes is well studied, the role of sex as a modifying factor is underexplored. This study aims to assess how sex influences brain and inflammatory markers in MDD. We utilized voxel-based and surface-based morphometry to analyze gray matter (GM) structure, along with GM-based spatial statistics (GBSS) to examine GM microstructure among treatment-naive patients with depression (n = 174) and age-matched healthy controls (n = 133). We uncovered sex-by-diagnosis interactions in several limbic system structures, the frontoparietal operculum and temporal regions. Post hoc analyses revealed that male patients exhibit pronounced brain abnormalities, while no significant differences were noted in females despite their higher depressive scores. Additionally, heightened inflammation levels in MDD were observed in both sexes, with sex-specific effects on sex-specific brain phenotypes, particularly including a general negative correlation in males. Intriguingly, mediation analyses highlight the specific role of the parahippocampal gyrus (PHG) in mediating interleukin (IL)-8 and depression in men. The findings suggest that in clinical practice, it would be beneficial to prioritize sex-specific assessments and interventions for MDD. This includes recognizing the possibility that male patients may experience significant brain alterations, especially when identifying male patients who may underreport symptoms. Possible limitations encompass a small sample size and the cross-sectional design. In future research, the incorporation of longitudinal studies or diverse populations, while considering illness duration, will enhance our understanding of how inflammation interacts with brain changes in depression.

This study aimed to discriminate between neuroinflammation and neuronal degeneration in the white matter (WM) and gray matter (GM) of patients with Parkinson’s disease (PD) using free-water (FW) imaging. Analysis using tract-based spatial statistics (TBSS) of 20 patients with PD and 20 healthy individuals revealed changes in FW imaging indices (i.e., reduced FW-corrected fractional anisotropy (FAT), increased FW-corrected mean, axial, and radial diffusivities (MDT, ADT, and RDT, respectively) and fractional volume of FW (FW) in somewhat more specific WM areas compared with the changes of DTI indices. The region-of-interest (ROI) analysis further supported these findings, whereby those with PD showed significantly lower FAT and higher MDT, ADT, and RDT (indices of neuronal degeneration) in anterior WM areas as well as higher FW (index of neuroinflammation) in posterior WM areas compared with the controls. Results of GM-based spatial statistics (GBSS) analysis revealed that patients with PD had significantly higher MDT, ADT, and FW than the controls, whereas ROI analysis showed significantly increased MDT and FW and a trend toward increased ADT in GM areas, corresponding to Braak stage IV. These findings support the hypothesis that neuroinflammation precedes neuronal degeneration in PD, whereas WM microstructural alterations precede changes in GM.

We observed the characteristics of white matter fibers and gray matter in multiple sclerosis patients, to identify changes in diffusion tensor imaging fractional anisotropy values following white matter fiber injury. We analyzed the correlation between fractional anisotropy values and changes in whole-brain gray matter volume. The participants included 20 patients with relapsing-remitting multiple sclerosis and 20 healthy volunteers as controls. All subjects underwent head magnetic resonance imaging and diffusion tensor imaging. Our results revealed that fractional anisotropy values decreased and gray matter volumes were reduced in the genu and splenium of corpus callosum, left anterior thalamic radiation, hippocampus, uncinate fasciculus, right corticospinal tract, bilateral cingulate gyri, and inferior longitudinal fasciculus in multiple sclerosis patients. Gray matter volumes were significantly different between the two groups in the right frontal lobe（superior frontal, middle frontal, precentral, and orbital gyri）, right parietal lobe（postcentral and inferior parietal gyri）, right temporal lobe（caudate nucleus）, right occipital lobe（middle occipital gyrus）, right insula, right parahippocampal gyrus, and left cingulate gyrus. The voxel sizes of atrophic gray matter positively correlated with fractional anisotropy values in white matter association fibers in the patient group. These findings suggest that white matter fiber bundles are extensively injured in multiple sclerosis patients. The main areas of gray matter atrophy in multiple sclerosis are the frontal lobe, parietal lobe, caudate nucleus, parahippocampal gyrus, and cingulate gyrus. Gray matter atrophy is strongly associated with white matter injury in multiple sclerosis patients, particularly with injury to association fibers.

Moyamoya disease and cerebrovascular atherosclerotic disease are both chronic ischemic diseases with similar presentations of vascular cognitive impairment. The aim of the present study was to investigate the patterns of microstructural damage associated with vascular cognitive impairment in the two diseases. The study recruited 34 patients with moyamoya disease (age 43.9 ± 9.2 years; 20 men and 14 women, 27 patients with cerebrovascular atherosclerotic disease (age: 44.6 ± 7.6 years; 17 men and 10 women), and 31 normal controls (age 43.6 ± 7.3 years; 18 men and 13 women) from Huashan Hospital of Fudan University in China. Cognitive function was assessed using the Mini-Mental State Examination, long-term delayed recall of Auditory Verbal Learning Test, Trail Making Test Part B, and the Symbol Digit Modalities Test. Single-photon emission-computed tomography was used to examine cerebral perfusion. Voxel-based morphometry and tract-based spatial statistics were performed to identify regions of gray matter atrophy and white matter deterioration in patients and normal controls. The results demonstrated that the severity of cognitive impairment was similar between the two diseases in all tested domains. Patients with moyamoya disease and those with cerebrovascular atherosclerotic disease suffered from disturbed supratentorial hemodynamics. Gray matter atrophy in bilateral middle cingulate cortex and parts of the frontal gyrus was prominent in both diseases, but in general, was more severe and more diffuse in those with moyamoya disease. White matter deterioration was significant for both diseases in the genu and body of corpus callosum, in the anterior and superior corona radiation, and in the posterior thalamic radiation, but in moyamoya disease, it was more diffuse and more severe. Vascular cognitive impairment was associated with regional microstructural damage, with a potential link between, gray and white matter damage. Overall, these results provide insight into the pathophysiological nature of vascular cognitive impairment. This study was approved by the Institutional Review Board in Huashan Hospital, China (approval No. 2014-278). This study was registered with ClinicalTrials.gov on December 2, 2014 with the identifier NCT02305407.