Background and aimsIn recent years, the study of brain structural changes in individuals experiencing suicidal ideation and depression has attracted increasing interest. This study investigated changes in gray and white matter volumes among different groups. We recruited 86 patients, including 26 healthy controls (HCs), 29 with depression (NS), 18 with suicidal ideation (SI), and 13 improved (IM), to further understand the impact of treatment on suicidal ideation.Materials and methodsWe used MRI to analyze four groups of participants at two time points over one-year intervals. Additionally, evaluations were conducted using clinical assessment scales (HAM-D, HADS-A, BSS, RRS).ResultsRepeated measures Analysis of Covariance (ANCOVA) and paired t tests revealed significant changes in brain volume across different groups at two time points. Notable differences were observed in regions such as the cingulate gyrus, corpus callosum, insula, amygdala, and hippocampus, indicating dynamic structural changes related to suicidal ideation and its treatment.ConclusionsOur findings highlight the potential value of brain structural changes in evaluating depression and suicidal ideation, supporting the effectiveness of early interventions in improving mental health. The observed alterations in gray and white matter emphasized the importance of targeted treatments for better patient outcomes.Supplementary InformationThe online version contains supplementary material available at 10.1007/s44192-025-00334-y.

Effects of sMRI-guided rTMS on brain function and structure in major depressive disorder.

Atrophy patterns of gray matter volume and the correlation with the disease duration in the cerebellum and hippocampal subregions in mesial temporal lobe epilepsy.

Elevated levels of blood-based biomarkers such as neurofilament light chain (NfL) and neuron-specific enolase (NSE) are associated with poor neurological outcome after out-of-hospital cardiac arrest (OHCA). This study investigates the relationship between regional grey matter volume reduction and levels of glial fibrillary acidic protein (GFAP), NfL, NSE, and total-tau (t-tau) protein. This substudy of the Xe-Hypotheca trial included 110 patients randomized to receive either inhaled xenon with target temperature management (TTM) at 33°C for 24h (n = 55) or TTM alone (n = 55). Voxel-based morphometry was used to assess grey matter volume changes in MRI scans acquired 36-52h and 10days after OHCA in 45 survivors. Blood biomarkers were measured upon intensive care unit arrival and at 24, 48 and 72h post-OHCA. NfL levels positively correlated with grey matter volume reduction in the thalamus and cingulate cortex at 24h post-OHCA. T-tau showed more extensive pattern of significant correlations, increasing in both magnitude and spatial extent from baseline to 48h post-OHCA. No significant biomarker-volume associations were observed for GFAP or NSE, and no treatment group differences were detected. Elevated NfL and t-tau levels were associated with region-specific grey matter volume reduction within the first 10days after OHCA. Among the four biomarkers studied, t-tau demonstrated the strongest and most widespread associations, suggesting its potential as a marker for early ischemic grey matter volume reduction after OHCA. ClinicalTrials.gov NCT00879892, 13/04/2009.

Background and purposeA proportion of individuals recovering from COVID-19 continue to experience persistent symptoms, including fatigue and cognitive difficulties — a syndrome commonly referred to as Post-COVID condition (PCC), which affects an estimated 2–10% of cases. In this study, we evaluated cerebral blood flow (CBF) to better understand the pathophysiological mechanisms underlying PCC.Materials and methodsIn this prospective, monocentric study, we analyzed clinical and cerebral blood flow (CBF) data from a cohort of 55 patients who met the WHO diagnostic criteria for Post-COVID condition (PCC) and underwent MRI approximately 11 months after a positive PCR test for SARS-CoV-2. These PCC patients were compared to a matched control group of 36 individuals who had contracted COVID-19 but did not develop PCC. CBF was assessed using arterial spin labeling (ASL), a promising non-invasive technique that provides high spatial resolution for quantifying cerebral blood flow. Additionally, we examined changes in gray matter volume and atrophy using FreeSurfer-based cortical morphometry. We further explored the relationship between regional CBF alterations and clinical symptoms, including cognitive and olfactory function, as well as fatigue.ResultsIn our cohort, 59% of PCC patients could not return to their previous level of independence or employment due to symptoms, and 81% reported fatigue on the WEIMuS questionnaire. Conventional MRI showed no evidence of cortical atrophy. While no significant differences in regional CBF emerged after FDR correction, a more explorative threshold (p < 0.005) revealed reduced CBF in the right angular and middle occipital gyri in PCC patients. Fatigue, as assessed by the WEIMuS, was significantly correlated with reduced CBF in the right occipital regions, particularly for physical fatigue, but no associations were found with cognitive or olfactory performance.ConclusionIn PCC patients, fatigue was associated with reduced perfusion in right-sided occipital regions, suggesting a potential pathophysiological basis for this symptom. These findings may also provide an imaging biomarker to aid in the diagnosis of PCC.

Amyloid PET predicts atrophy in older adults without dementia: Results from the AMYPAD Prognostic & Natural History study

Post-COVID-19 olfactory dysfunction (PCOD) has been associated with structural brain changes, but the underlying molecular mechanisms and their relationship to gray matter volume (GMV) changes remain unclear. We included 36 patients with PCOD and 40 healthy controls. All patients underwent olfactory psychophysical testing (Sniffin' Sticks) and a visual analogue scale (VAS) assessment for olfactory function. GMV values for 34 brain regions were extracted, and Spearman's correlation analysis was performed with olfactory psychophysical testing scores. Partial least squares regression (PLS) was applied to explore the relationship between regional GMV differences and gene expression patterns. Gene set enrichment analysis was performed to identify relevant biological processes and cell types. PCOD patients showed increased GMV in the entorhinal cortex (t = 3.065, p = 0.003), positively correlated with the VAS score for olfactory function (r = 0.37, p = 0.028) and Sniffin' Sticks Test total score (r = 0.37, p = 0.026). PLS analysis identified gene expression patterns that were significantly associated with regional GMV changes. Enrichment analysis revealed that genes linked to GMV changes were enriched for biological processes related to "inorganic ion transmembrane transport" and "regulation of protein transport". Additionally, these genes were highly expressed in GABAergic neurons. These findings provide mechanistic insights into the relationship between altered brain structure and gene expression in PCOD, highlighting the involvement of specific biological pathways and cell types in the pathophysiology of olfactory dysfunction following COVID-19.

Brain structural and functional alterations in chronic non-specific low back pain: A case-control study.

It has been revealed that brain gray matter volume (GMV) abnormalities are present in patients with hepatic encephalopathy (HE). However, the GMV alterations in HE that have been uncovered are inconsistent, and their correlation with gene expression profiles is still unknown.We conducted a quantitative neuroimaging meta-analysis on seven studies, involving 142 HE individuals and 193 HCs, to identify consistent patterns of GMV alterations in HE. We then utilized the Allen Human Brain Atlas database to investigate transcriptome-neuroimaging spatial correlations, exploring gene expression profiles related with GMV changes in HE. Functional enrichment analyses were further performed to identify biological significance of the GMV-related genes.Compared with healthy controls, patients with HE exhibited decreased GMV primarily in the bilateral cerebellum, basal nuclei, insula, cingulate / paracingulate gyri (the anterior and the median), superior frontal gyrus (medial), precuneus and right inferior frontal gyrus. While the GMV of bilateral thalamus and right lingual gyrus were observed to increase in HE patients. Moreover, we revealed spatial associations between brain structural changes and transcriptional profiles of 2035 genes, which were enriched in specific biological processes in HE.Our findings improved the understanding of GMV abnormalities in HE and provided insights into the transcriptional expression patterns underlying these alterations.

Association between sleep disturbances and gray matter volume in individuals at clinical high-risk for psychosis and healthy controls: A longitudinal MRI study (NAPLS-3).

Evaluating the role of anti-EBV antibodies as biomarkers for the evolution of multiple sclerosis: A longitudinal study.

ABSTRACTThe tremor‐dominant (TD) subtype of Parkinson's disease (PD) is characterized by prominent tremor symptoms. However, the temporal and causal relationships between brain structural alterations in TD patients remain unexplored. A total of 61 TD patients and 61 matched healthy controls (HCs) were included in this study. The gray matter volume (GMV) of the bilateral precuneus (PCUN) was significantly reduced in TD patients. A structural covariance network analysis seeded with the left pallidum (PAL.L), which had the most significant differences, revealed a substantial reduction in covariance with precentral gyrus in TD patients. We performed a causal structural covariance network analysis using the TD duration as a pseudotime series. The PCUN, with the highest out‐degree in the cortex, regulates numerous regions, including the supplementary motor area and the extensive temporal lobe. Machine learning was utilized to construct a model that accurately assesses the surgical prognosis based on the above cortical volume and clinical scale, with the aim of assisting in clinical deep brain stimulation (DBS) treatment. These findings suggested a progressive pattern of GMV changes extending from the PAL.L to the PCUN region and continuing to other brain regions, providing insights into the progression of TD and enhancing DBS treatment strategies.

BackgroundWith the development of spaceflight, scientists have gradually realized that long-term microgravity can alter the brain’s structure, which may affect the stability of brain function and, in turn, cognition and many other behaviors.ObjectiveBy quantitatively analyzing the effects of microgravity on brain gray matter volume, fiber tracts, and resting-state neural functional activity, this study preliminarily explores the dynamic changes in brain tissue structure and their relationships during simulated microgravity.MethodsSix male rhesus macaques were included in the study and underwent −10° head-down bed rest (HDBR) for 42 days as a terrestrial analog of the microgravity environment. Multimodal magnetic resonance imaging (MRI) was performed 3 days before HDBR, 21 days after HDBR, and 42 days after HDBR. Voxel-based morphometry (VBM) analysis was used to compare differences in brain gray matter volume. Differences in the fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were investigated using tract-based spatial statistic (TBSS) analysis. Resting-state functional MRI was used to compare differences in local neural activity.ResultsDuring simulated microgravity, significant changes in gray matter volume were found in the right substantia innominate of the basal forebrain, right insula, left putamen, and left occipital gyrus. A significant decrease in FA and AD was found during simulated microgravity, specifically in the left inferior longitudinal fasciculus, left fornix, left corticospinal tract, left inferior longitudinal fasciculus, left superior longitudinal fasciculus, left frontal aslant tract, right uncinate fasciculus, and bilateral inferior fronto-occipital fasciculus regions. A significant decrease in MD and RD was widely observed in the left inferior longitudinal fasciculus, middle cerebellar peduncle, bilateral frontal aslant tract regions, bilateral anterior thalamic radiation, and bilateral uncinate fasciculus. Regional homogeneity (ReHo) in the left thalamic reticular nucleus continuously increased during simulated microgravity conditions.ConclusionUsing multimodality MRI, this study indicated that simulated microgravity might cause widespread abnormalities through neuroplasticity, especially in brain regions in charge of visuospatial awareness and voluntary motion. There may exist a complex functional compensation between the reconstruction of gray and white matter and the rearrangement of neural connections.

Declines in everyday cognitive functioning are a common occurrence in late life. The present study sought to understand how informant-rated everyday cognitive abilities related to memory, language, spatial skills, planning, organization, and divided attention-as measured by the Everyday Cognition (ECog) scale-change over time in a diverse sample of older adults. Participants (N = 891) from the University of California Davis Alzheimer's Disease Research Center longitudinal cohort (Mage = 76.1, SDage = 7.4) were followed for an average of 4.4 years with annual ECog assessments. Multilevel beta regression was used to model ECog scores as a function of time, cognitive domain, diagnosis change, and-in a neuroimaging subsample (N = 264)-cross-sectional and longitudinal total gray matter and hippocampus volume. ECog domains changed at different rates when modeled as a function of diagnosis change; differences in domain were most apparent in the stable mild cognitive impairment (MCI)-to-MCI and MCI-to-dementia conversion groups. By contrast, ECog domains changed at the same rate when modeled as a function of baseline gray matter volume and longitudinal gray matter volume change, corresponding to other research suggesting that cognitive domains change at relatively uniform rates over time. In separate models, total gray matter and hippocampus atrophy were salient predictors of ECog score changes. At baseline, hippocampus volume was the strongest predictor of ECog intercepts. Although some caution is warranted interpreting score changes due to floor and ceiling effects, the ECog appears sensitive to underlying gray matter atrophy and change in clinical disease severity when used longitudinally. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

BackgroundAdenomyosis is a prevalent gynecological condition among women of reproductive age and is commonly associated with heavy menstrual bleeding, severe dysmenorrhea, and infertility. These symptoms impose a substantial burden on both physical health and psychological well-being. Despite increasing recognition of its clinical impact, it remains unclear whether dysmenorrhea in adenomyosis is accompanied by structural brain alterations. Therefore, the present study aims to investigate whether adenomyosis-related dysmenorrhea is associated with changes in brain structure. Understanding such alterations may provide novel insights into the neural mechanisms underlying chronic pain and emotional disturbances in affected patients.MethodsFifty-one patients with adenomyosis-associated dysmenorrhea (AAD) and 51 demographically matched healthy controls (HCs) were recruited. Voxel-based morphometry was used to identify differences in gray matter volume (GMV). Between-group differences were analyzed using two-sample t-tests, and partial correlation analyses were conducted to assess the relationships between altered GMV and clinical symptoms within the AAD group.ResultsCompared with HCs, patients with AAD exhibited significant GMV changes in the right fusiform gyrus, right parahippocampal gyrus, right lingual gyrus, left superior frontal gyrus, and bilateral thalamus. Notably, decreased GMV in the right fusiform and right parahippocampal gyri was significantly correlated with pain and emotional scale scores.ConclusionsThe observed gray matter abnormalities may underlie the neural mechanisms of pain and emotional disturbances in patients with AAD. These findings enhance our understanding of the brain’s role in the interaction between chronic pain and emotional symptoms in AAD.

Neuron loss is a key feature of neurodegenerative diseases often leading to brain atrophy detectable through magnetic resonance imaging (MRI). Various brain atrophy measures are essential in research of Alzheimer’ disease (AD) and related dementias. This study aims to forecast future annual percentage changes in hippocampal, ventricular, and total gray matter (TGM) volumes in individuals with varying cognitive statuses, from healthy to dementia. We developed a machine learning model using elastic net linear regression and tested two approaches: (1) a baseline model using predictors from a single-time-point and (2) a longitudinal model using predictors derived from longitudinal MRI. Both approaches were evaluated with MRI-only models and models that combined MRI with additional risk factors (age, sex, APOE4, and baseline diagnosis). Cross-validated Pearson correlation scores between predicted and actual annual percentage changes were 0.62 for the hippocampus, 0.51 for the ventricles, and 0.41 for TGM, using the longitudinal MRI + risk factor model. Longitudinal models consistently outperformed baseline models, and models including risk factors outperformed the MRI only model. Validation using an external dataset confirmed these findings, highlighting the value of predictors derived based on longitudinal data. We further studied the value of the predicted atrophy/enlargement rates for clinical status progression prediction across three different datasets. Predicted atrophy was a consistently better indicator of progression to mild cognitive impairment and dementia than present-day regional volumes, with the longitudinal atrophy prediction model typically outperforming the baseline model in terms of clinical status prediction. Future atrophy prediction has significant potential for assessing the risk of cognitive decline, even in cognitively unimpaired individuals, and can aid in selecting participants for clinical trials of disease-modifying drugs for AD.

ABSTRACTBackgroundImpaired insight can be understood clinically as a loss of ability to appropriately recognize one's own disease status. Investigating insight in Alzheimer's disease (AD) and its relation to longitudinal changes in brain structure is important to understand the disease progression.ObjectiveTo examine how the character of insight changes with disease stage and assess whether baseline levels of impaired insight can predict rate of brain atrophy across a period of 30 months in a cohort of subjects consisting of subjective memory complaint (SMC), mild cognitive impairment (MCI), AD, and cognitively normal (CN) controls.MethodsData from 794 eligible participants were extracted from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Insight levels were estimated by the Measurement of Everyday Cognition (ECog). Impairment was further categorized into overestimation or underestimation of ability. Brain atrophy rates were estimated by measuring change in gray matter volume within 30 months.ResultsOverestimating ability was significantly correlated with increased whole‐brain atrophy rates (p < 0.001) independent of general cognitive decline. Overestimation of ability exhibited significant correlations with increased atrophy in specific regions of the brain including the medial temporal lobe, fusiform gyrus, and hippocampus.DiscussionThe present results suggest a statistically significant correlation between overestimation of ability and increased rates of subsequent brain atrophy. This is particularly notable in regions of the brain such as the hippocampus. However, further study into the phenomenon of insight and its progression over the disease course is required before its potential clinical utility can be fully assessed.

BackgroundThe thalamus, along with its component nuclei, possesses extensive connections with various brain regions and is engaged in diverse functions. However, it is unknown whether the gray matter volume (GMV) covariance networks of thalamic subfields are selectively affected in chronic capsular stroke.MethodsWe recruited 45 patients with chronic right capsular strokes (CS) and 93 normal controls (NC) from three centers. The thalamus was segmented into 25 subfields using FreeSurfer (v7.1.1). A general linear model was applied to investigate intergroup differences in the GMV covariance network of each thalamic subfield with each voxel of the entire brain between CS and NC, correcting for confounders such as age, gender, total intracranial volume (TIV), and scanners (voxel-wise p < 0.001, cluster-wise FWE corrected p < 0.05).ResultsOur findings revealed that all 25 ipsilesional thalamic subfields in CS were atrophied (p < 0.05, FDR correction). Among these, 16 ipsilesional thalamic subfields (including AV, LD, LP, VLa, VLp, VPL, VM, CeM, CL, MDm, LGN, PuM, PuI, CM, Pf, and Pt) exhibited significantly subfield-specific increased GMV covariance connectivity with the anterior orbital gyrus, superior occipital gyrus, calcarine, anterior cingulate cortex, precentral gyrus, and other regions. Additionally, although none of the contralesional thalamic subfields demonstrated regional GMV changes, 3/25 showed subfield-specific increased GMV covariance connectivity with the ipsilesional anterior orbital gyrus and subcortex.ConclusionThe GMV covariance networks of thalamic subfields are selectively involved in patients with chronic capsular stroke, which affect not only the ipsilesional thalamic subfields but also the contralesional ones.

Aging has important impacts on both the function and structure of the brain, yet the interplay between these changes remains unclear. Here, we present a unified framework including both single-modal and multimodal age predictions using a large UK Biobank dataset (27,793 healthy subjects, 49 to 76 years) to identify and validate brain functional network connectivity (FNC) and gray matter volume (GMV) changes associated with aging, then propose a novel analysis method to reveal various joint aging patterns, and finally investigate the association between joint function–structure changes and cognitive declines. Multimodality outperforms single modality in the age prediction, underscoring the significance of multimodal aging-related changes. Aging primarily induces synergistic changes, with both FNC and GMV decreased in the cerebellum, frontal pole, paracingulate gyrus, and precuneus cortex, indicating consistent degeneration in motor control, sensory processing, and emotional regulation, and contradictory changes with increased FNC magnitude but decreased GMV in the occipital pole, lateral occipital cortex, and frontal pole, acting as a compensatory mechanism as one ages to preserve visual acuity, cognitive ability, and behavioral modulation. Particularly, joint changes, with both FNC and GMV decreased in the crus I cerebellum and the paracingulate gyrus, show a strong Pearson correlation with the reaction time. In summary, our study unveils diverse joint function–structure changes, providing strong evidence for understanding distinct cognitive deteriorations during aging.

Brain age estimated from structural magnetic resonance images is commonly used as a biomarker of biological aging and brain health. Ideally, as a clinically valid biomarker, brain age should indicate the current state of health and be predictive of future disease onset and detrimental changes in brain biology. In this preregistered study, we evaluated and compared the clinical validity, i.e., diagnostic and prognostic performance, of six publicly available brain age prediction packages using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Baseline brain age differed significantly between groups consisting of individuals with normal cognitive function, mild cognitive impairment, and Alzheimer’s disease for all packages, but with comparable performance to estimates of gray matter volume. Further, brain age estimates were not centered around zero for cognitively normal subjects and showed considerable variation between packages. Finally, brain age was only weakly correlated with disease onset, memory decline, and gray matter atrophy within four years from baseline in individuals without neurodegenerative disease. The systematic discrepancy between chronological age and brain age among healthy subjects, combined with the weak associations between brain age and longitudinal changes in memory performance or gray matter volume, suggests that the current brain age estimates have limited clinical validity as a biomarker for biological aging.