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8 recordsLinked to original sources
PubMed2026

Bidirectional causal relationships between plasma proteins, neuroimaging metrics and risk of Alzheimer's disease.

BACKGROUND: Changes in neuroimaging metrics are among the first detectable pathophysiological alterations in Alzheimer's disease (AD). Proteins are closely linked to fluctuations in neuroimaging metrics. Therefore, the analysis of the proteomic signature associated with neuroimaging metrics holds significant promise for uncovering therapeutic targets that contribute to AD. METHODS: GWAS data concerning the Brain Imaging Data Structure (BIDs). The AD cohort comprised a total of 401,661 individuals diagnosed with AD, alongside 10,520 control participants. For a bidirectional MR analysis involving neuroimaging metrics, proteomics, and AD, the methods utilized included inverse variance weighted (IVW), MR Egger, weighted median, weighted mode, and the Wald ratio approaches. RESULTS: We identified 12 neuroimaging metrics that demonstrate significant relevance to AD (thickness of the left total hemisphere, volume of the right thalamus, and et al.). These metrics are structural magnetic resonance imaging (MRI) biomarkers that remain stable throughout the entire course of AD, from the preclinical stage through mild cognitive impairment (MCI) to dementia. Additionally, we found a substantial number of 1633 proteins that also show a noteworthy causal relationship with AD. Functional enrichment analysis indicated that these proteins were predominantly focused within various pathways linked to AD, encompassing those involved in the synaptic vesicle cycle, synaptic membranes, neurotransmitter release, and the activity of GABA receptors. In addition, our research indicates that the significant relationships observed between the identified proteins and AD are influenced by neuroimaging metrics. Notably, we found that these neuroimaging metrics play a crucial role in mediating a substantial 67% of the inverse relationship that exists between PTPRC and the phenotypic characteristics associated with AD. CONCLUSIONS: This study successfully establishes a connection between proteomic and neuroimaging metrics, as well as the AD that influence them. By creating this relationship, the research offers important information that aids in comprehending the intricate mechanisms involved in AD.

Alzheimer Disease↗
PubMed2026

Systematic proteomic analysis of neuroimaging metrics identifies therapeutic targets for pituitary neuroendocrine.

The relationship between proteomics and neuroimaging metrics (NIMs) is still not fully understood. By examining the specific proteins expressed in different NIMs, researchers can gain insights into how these NIMs contribute to pituitary neuroendocrine tumors (PitNETs), ultimately enabling the development of targeted interventions and treatments. We identified 15 significantly NIMs and 18 proteins that exhibit a noteworthy causal relationship with the risk of developing PitNETs by forward MR analysis. Additionally, 10 proteins and one distinct neuroimaging metric with PitNETs. Then, the MR results indicated the identification of 33 significant relationships, which connect proteins with NIMs across five distinct categories. Then, we discovered that NIMs are capable of mediating 63% of the inverse relationship observed between WNT3 and the phenotypic characteristics of PitNETs. The results also suggested that WNT3 was associated with hypothalamic function, pituitary function, thyroid function, adrenal function, and gonadal function. Additionally, WNT3 expression was higher in PitNETs and was verified in multiple datasets. This research effectively connects the roles of protein markers with the structures of the brain and the PitNETs that can affect it. By establishing this link, the study provides valuable insights that can help in understanding the complex mechanisms that contribute to PitNETs.

Proteomics↗
PubMed2025

A randomized controlled trial to unveil the influence of an exercise intervention on brain integrity and gut microbiome structure in individuals with HIV.

OBJECTIVE: Exercise intervention programs enhance physical fitness, cognition, neuroimaging measures, and alter the structure of the gut microbiome in individuals without HIV. However, interventional studies exploring the effects of exercise in persons with HIV (PWH) have not included neuroimaging or gut microbiome analyses. DESIGN: A randomized controlled trial conducted at Washington University in St. Louis, MO, USA. METHODS: 65 PWH (aged ≥40 years, self-reported sedentary lifestyle) were randomly assigned to a 6-month cardiorespiratory and resistance training (EXS) or stretching control (SIS) intervention in a 2 : 1 ratio. Longitudinal change in cognition, cerebral blood flow (CBF), physical and cardiorespiratory fitness, and gut microbiome diversity and composition were examined among participants ( n  = 62) who completed any portion of the intervention (ClinicalTrials.gov: NCT02663934). RESULTS: Better fitness and better cognitive performance were associated with greater phylogenetic diversity in gut microbiome composition at baseline. Longitudinal findings indicated slight but significant improvements in psychomotor speed and executive function, reductions in body mass index, improvements in physical fitness, and increased gut microbiome diversity. These changes were observed regardless of assigned intervention group. There were no observed changes in CBF for either group. CONCLUSIONS: These findings highlight physical fitness as a modifiable factor in PWH that may improve cognitive performance and change gut microbiome composition. Both interventions were beneficial, suggesting light stretching exercise or study participation alone could have been sufficient to introduce positive cognitive shifts in previously sedentary PWH. Longer interventions with more participants are needed to identify changes in neuroimaging metrics related to brain integrity.

Humans↗
PubMed2024

Free-water: A promising structural biomarker for cognitive decline in aging and mild cognitive impairment.

Diffusion MRI derived free-water (FW) metrics show promise in predicting cognitive impairment and decline in aging and Alzheimer's disease (AD). FW is sensitive to subtle changes in brain microstructure, so it is possible these measures may be more sensitive than traditional structural neuroimaging biomarkers. In this study, we examined the associations among FW metrics (measured in the hippocampus and two AD signature meta-ROIs) with cognitive performance, and compared FW findings to those from more traditional neuroimaging biomarkers of AD. We leveraged data from a longitudinal cohort (nparticipants = 296, nobservations = 870, age at baseline: 73 ± 7 years, 40% mild cognitive impairment [MCI]) of older adults who underwent serial neuropsychological assessment (episodic memory, information processing speed, executive function, language, and visuospatial skills) and brain MRI over a maximum of four time points, including baseline (n = 284), 18-month (n = 246), 3-year (n = 215), and 5-year (n = 125) visits. The mean follow-up period was 2.8 ± 1.3 years. Structural MRI was used to quantify hippocampal volume, in addition to Schwarz and McEvoy AD Signatures. FW and FW-corrected fractional anisotropy (FAFWcorr) were quantified in the hippocampus (hippocampal FW) and the AD signature areas (SchwarzFW, McEvoyFW) from diffusion-weighted (dMRI) images using bi-tensor modeling (FW elimination and mapping method). Linear regression assessed the association of each biomarker with baseline cognitive performance. Additionally, linear mixed-effects regression assessed the association between baseline biomarker values and longitudinal cognitive performance. A subsequent competitive model analysis was conducted on both baseline and longitudinal data to determine how much additional variance in cognitive performance was explained by each biomarker compared to the covariate only model, which included age, sex, race/ethnicity, apolipoprotein-ε4 status, cognitive status, and modified Framingham Stroke Risk Profile scores. All analyses were corrected for multiple comparisons using an FDR procedure. Cross-sectional results indicate that hippocampal volume, hippocampal FW, Schwarz and McEvoy AD Signatures, and the SchwarzFW and McEvoyFW metrics are all significantly associated with memory performance. Baseline competitive model analyses showed that the McEvoy AD Signature and SchwarzFW explain the most unique variance beyond covariates for memory (ΔRadj 2 = 3.47 ± 1.65%) and executive function (ΔRadj 2 = 2.43 ± 1.63%), respectively. Longitudinal models revealed that hippocampal FW explained substantial unique variance for memory performance (ΔRadj 2 = 8.13 ± 1.25%), and outperformed all other biomarkers examined in predicting memory decline (pFDR = 1.95 x 10-11). This study shows that hippocampal FW is a sensitive biomarker for cognitive impairment and decline, and provides strong evidence for further exploration of this measure in aging and AD.

Alzheimer’s disease (AD)↗
PubMed2025

Diffusion tensor imaging in Chediak Higashi Disease.

AIM: To define the natural history of diffusion tensor imaging (DTI) in Chediak-Higashi Disease (CHD) participants in relation to normative development. METHODS: Twenty-five DTI scans from 15 CHD participants were compared with 100 DTI scans from 100 neurotypical controls (NC). Comparisons were evaluated for DTI metrics including fractional anisotropy (FA), and mean, axial, and radial diffusivity (MD, AD, RD, respectively). Correlational tractography was also performed to identify group differences between CHD and NC. RESULTS: Pediatric CHD participants had DTI metrics similar to NC, however, progressive pathogenic increases in MD, AD, and RD were observed in CHD participants compared to NC in white matter pathways of the whole brain, corpus callosum, and cerebellum. Correlational fiber tractography identified fiber tracts with decreased FA, and increased MD, AD, and RD in CHD compared to NC. INTERPRETATION: Progressive deviations in DTI metrics highlight the progressive neurodegeneration of CHD. Aberrations in cerebellar white matter is reflective of the clinical neurologic phenotype of CHD including cerebellar dysfunction and cognitive decline. The corollary of progressive aberrations in DTI metrics and progressive clinical neurodegeneration suggest DTI may be a suitable neuroimaging marker for CHD. Future studies should evaluate functional magnetic resonance imaging and volumetric studies in this cohort.

Chediak-Higashi Disease↗
PubMed2026

Complement component C4 and neuroimaging in psychiatry: A systematic review.

INTRODUCTION: Genomic, transcriptomic, and proteomic studies suggest that the complement system contributes to the pathophysiology of various psychiatric disorders partly through neurodevelopmental effects linked to C4A protein levels variations. We conducted a systematic review to characterize how brain micro- and macrostructure and connectivity vary with proxies of in vivo brain C4A protein levels in both psychiatric and general-population cohorts. METHODS: We used Medline, Web of Science, and Embase, and included all studies published before April 14, 2025. Inclusion criteria were: (1) inclusion of healthy controls and/or individuals with psychiatric disorders assessed according to recognized diagnostic manuals (DSM or ICD); (2) use of MRI-based neuroimaging; and (3) use of genomic, transcriptomic and/or proteomic approaches as proxies of in vivo brain C4A proteins levels. RESULTS: From 317 identified articles, 11 were included. Associations between C4A levels and brain structure were heterogeneous across regions. Only the mOFC, dlPFC, and entorhinal cortex were implicated in more than one study. Findings for the mOFC and dlPFC varied by the type of metrics and clinical status, whereas higher C4A levels were more consistently associated with smaller entorhinal cortex surface area and cortical thickness in pediatric, middle-aged, and older general-population cohorts. In addition, one study found higher genetically predicted C4A expression to be associated with higher TSPO levels. CONCLUSION: The limited number of available studies and their methodological heterogeneity make synthesis challenging. However, biological hypotheses such as excessive synaptic pruning or broader inflammatory effects on the brain may provide plausible explanatory frameworks for the reported associations.

Humans↗
PubMed2026

Effects of strength and balance training on the structure of the aging brain.

BACKGROUND: While it is established that motor training induces structural changes in the brains of young adults, structural adaptations in aging brains are less studied. METHODS: This randomized controlled study investigated the impact of long-term strength and balance training on the structural plasticity in 60 elderly adults (64 - 82 years old, 70.6 ± 4.7) using multi-modal neuroimaging. We compared the effects of three months of strength training to balance training of the same duration and to a passive control group. Voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) were used to assess grey matter (GM) and white matter (WM) plasticity. White matter tract integrity (WMTI) modelling was employed to explore the microstructural underpinnings of white matter alterations. RESULTS: We found that strength training was associated with changes in diffusion metrics consistent with white matter microstructural remodeling, specifically increased extra-axonal axial diffusivity in the bilateral inferior fronto-occipital and longitudinal fasciculi. Additionally, both balance and strength training mitigated reductions in axonal water fraction in the splenium of the corpus callosum and the right posterior corona radiata observed in the control group. CONCLUSION: These results underscore the potential relevance of strength and balance training to induce beneficial neural plasticity by counteracting aging-related demyelination in the corpus callosum and highlight the specific role of strength training in facilitating white matter reorganization in key transmission fiber pathways.

Humans↗
PubMed2025

TMS-EEG in postictal psychosis of epilepsy.

BACKGROUND: Postictal psychosis (PIP) is a poorly understood complication affecting 2 % of individuals with epilepsy. Genomic and neuroimaging studies suggest parallels with schizophrenia. OBJECTIVES: To determine whether Transcranial Magnetic Stimulation coupled with Electroencephalography (TMS-EEG), can reveal schizophrenia-like changes in PIP, especially in Natural Frequency (NF), gamma band Event-Related Spectral Perturbation (ERSP), the N100 peak, and global mean field power (GMFP). METHODS: We applied TMS-EEG targeting the non-dominant hemisphere premotor area in people with focal epilepsy (PWE) with a history of PIP (n = 7) and PWE without any history of psychosis (n = 14). Two-tailed t-tests were applied to TMS-EEG metrics previously studied in schizophrenia to look for differences between the groups, with subgroup analyses excluding participants using benzodiazepines. RESULTS: Demographic and clinical characteristics were similar across the two groups. No significant differences were seen in NF (p = 0.98). We observed a delayed N100 peak latency in the PIP group when excluding those with regular benzodiazepine use (p = 0.05) and increased global mean field power during the 400-600 ms phase of the TEP (p = 0.02). Mean ERSP within the gamma band was lower in the PIP group, though this did not reach statistical significance (p = 0.08). CONCLUSION: This is the first study to apply TMS-EEG in individuals with PIP, demonstrating feasibility and providing methodological insights for future studies. Preliminary findings, including increased GMFP and delayed N100 latency in PIP, suggest possible disruptions in cortical excitability similar to schizophrenia, warranting further investigation.

Humans↗