BACKGROUND: Changes in both the vascular system and brain tissues can occur after a prior episode of coronavirus disease 2019 (COVID-19), detectable through modifications in diffusion parameters using magnetic resonance imaging (MRI) techniques. These changes in diffusion parameters may be particularly prominent in highly organized structures such as the corpus callosum (CC), including its major components, which have not been adequately studied following COVID-19 infection. Therefore, the study aimed to evaluate microstructural changes in whole-brain (WB) diffusion, with a specific focus on the CC. METHODS: A total of 101 probands (age range from 18 to 69 years) participated in this retrospective study, consisting of 55 volunteers and 46 post-COVID-19 patients experiencing neurological symptoms. The participants were recruited from April 2022 to September 2023 at the Institute for Clinical and Experimental Medicine in Prague, Czech Republic. All participants underwent MRI examinations on a 3T MR scanner with a diffusion protocol, complemented by additional MRI techniques. Two volunteers and five patients were excluded from the study due to motion artefacts, severe hypoperfusion or the presence of lesions. Participants were selected by a neurologist based on clinical examination and a serological test for COVID-19 antibodies. They were then divided into three groups: a control group of healthy volunteers (n=28), an asymptomatic group (n=25) with a history of infection but no symptoms, and a symptomatic group (n=41) with a history of COVID-19 and neurological symptoms. Symptomatic patients did not exhibit neurological symptoms before contracting COVID-19. Diffusion data underwent eddy current and susceptibility distortion corrections, and fiber tracking was performed using default parameters in DSI studio. Subsequently, various diffusion metrics, were computed within the reconstructed tracts of the WB and CC. To assess the impact of COVID-19 and its associated symptoms on diffusion indices within the white matter of the WB and CC regions, while considering age, we employed a statistical analysis using a linear mixed-effects model within the R framework. RESULTS: Statistical analysis revealed a significant difference in mean diffusivity (MD) between the symptomatic and control groups in the forceps minor (P=0.001) and CC body (P=0.003). In addition to changes in diffusion, alterations in brain perfusion were observed in two post-COVID-19 patients who experienced a severe course. Furthermore, hyperintense lesions were identified in subcortical and deep white matter areas in the vast majority of symptomatic patients. CONCLUSIONS: The main finding of our study was that post-COVID-19 patients exhibit increased MD in the forceps minor and body of the CC. This finding suggests a potential association between microstructural brain changes in post-COVID-19 patients and reported neurological symptoms, with significant implications for research and clinical applications.
Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
- MeSH
- algoritmy * MeSH
- dospělí MeSH
- hipokampus diagnostické zobrazování patologie MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie * MeSH
- mozek diagnostické zobrazování patologie MeSH
- neurozobrazování MeSH
- průřezové studie MeSH
- reprodukovatelnost výsledků MeSH
- schizofrenie * diagnostické zobrazování patologie MeSH
- šedá hmota * diagnostické zobrazování patologie MeSH
- strojové učení MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Evropa MeSH
- Severní Amerika MeSH
Brain activity during the resting state is widely used to examine brain organization, cognition and alterations in disease states. While it is known that neuromodulation and the state of alertness impact resting-state activity, neural mechanisms behind such modulation of resting-state activity are unknown. In this work, we used a computational model to demonstrate that change in excitability and recurrent connections, due to cholinergic modulation, impacts resting-state activity. The results of such modulation in the model match closely with experimental work on direct cholinergic modulation of Default Mode Network (DMN) in rodents. We further extended our study to the human connectome derived from diffusion-weighted MRI. In human resting-state simulations, an increase in cholinergic input resulted in a brain-wide reduction of functional connectivity. Furthermore, selective cholinergic modulation of DMN closely captured experimentally observed transitions between the baseline resting state and states with suppressed DMN fluctuations associated with attention to external tasks. Our study thus provides insight into potential neural mechanisms for the effects of cholinergic neuromodulation on resting-state activity and its dynamics.
- MeSH
- acetylcholin metabolismus MeSH
- default mode network fyziologie diagnostické zobrazování MeSH
- dospělí MeSH
- konektom * MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- modely neurologické * MeSH
- mozek * fyziologie diagnostické zobrazování MeSH
- nervová síť fyziologie diagnostické zobrazování MeSH
- odpočinek * fyziologie MeSH
- počítačová simulace MeSH
- výpočetní biologie MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mužské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- acetylcholin MeSH
BACKGROUND: Lateral ventricular enlargement represents a canonical morphometric finding in chronic patients with schizophrenia; however, longitudinal studies elucidating complex dynamic trajectories of ventricular volume change during critical early disease stages are sparse. METHODS: We measured lateral ventricular volumes in 113 first-episode schizophrenia patients (FES) at baseline visit (11.7 months after illness onset, SD = 12.3) and 128 age- and sex-matched healthy controls (HC) using 3T MRI. MRI was then repeated in both FES and HC one year later. RESULTS: Compared to controls, ventricular enlargement was identified in 18.6% of patients with FES (14.1% annual ventricular volume (VV) increase; 95%CI: 5.4; 33.1). The ventricular expansion correlated with the severity of PANSS-negative symptoms at one-year follow-up (p = 0.0078). Nevertheless, 16.8% of FES showed an opposite pattern of statistically significant ventricular shrinkage during ≈ one-year follow-up (-9.5% annual VV decrease; 95%CI: -23.7; -2.4). There were no differences in sex, illness duration, age of onset, duration of untreated psychosis, body mass index, the incidence of Schneiderian symptoms, or cumulative antipsychotic dose among the patient groups exhibiting ventricular enlargement, shrinkage, or no change in VV. CONCLUSION: Both enlargement and ventricular shrinkage are equally present in the early stages of schizophrenia. The newly discovered early reduction of VV in a subgroup of patients emphasizes the need for further research to understand its mechanisms.
- Klíčová slova
- First-episode schizophrenia, Longitudinal design, MRI, Negative symptoms, Ventricular volumes,
- MeSH
- dospělí MeSH
- lidé MeSH
- longitudinální studie MeSH
- magnetická rezonanční tomografie * MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mozkové komory diagnostické zobrazování patologie MeSH
- progrese nemoci MeSH
- schizofrenie * diagnostické zobrazování patologie patofyziologie MeSH
- studie případů a kontrol MeSH
- ventriculi laterales diagnostické zobrazování patologie MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: Negative symptoms (NS) represent a detrimental symptomatic domain in schizophrenia affecting social and occupational outcomes. AIMS: We aimed to identify factors from the baseline visit (V1) - with a mean illness duration of 0.47 years (SD = 0.45) - that predict the magnitude of NS at the follow-up visit (V3), occurring 4.4 years later (mean +/- 0.45). METHOD: Using longitudinal data from 77 first-episode schizophrenia spectrum patients, we analysed eight predictors of NS severity at V3: (1) the age at disease onset, (2) age at V1, (3) sex, (4) diagnosis, (5) NS severity at V1, (6) the dose of antipsychotic medication at V3, (7) hospitalisation days before V1 and; (8) the duration of untreated psychosis /DUP/). Secondly, using a multiple linear regression model, we studied the longitudinal relationship between such identified predictors and NS severity at V3 using a multiple linear regression model. RESULTS: DUP (Pearson's r = 0.37, p = 0.001) and NS severity at V1 (Pearson's r = 0.49, p < 0.001) survived correction for multiple comparisons. The logarithmic-like relationship between DUP and NS was responsible for the initial stunning incremental contribution of DUP to the severity of NS. For DUP < 6 months, with the sharpest DUP/NS correlation, prolonging DUP by five days resulted in a measurable one-point increase in the 6-item negative symptoms PANSS domain assessed 4.9 (+/- 0.6) years after the illness onset. Prolongation of DUP to 14.7 days doubled this NS gain, whereas 39 days longer DUP tripled NS increase. CONCLUSION: The results suggest the petrification of NS during the early stages of the schizophrenia spectrum and a crucial dependence of this symptom domain on DUP. These findings are clinically significant and highlight the need for primary preventive actions.
- Klíčová slova
- First-episode schizophrenia, duration of untreated psychosis, longitudinal study, negative symptoms, prediction,
- MeSH
- antipsychotika * terapeutické užití MeSH
- lidé MeSH
- multivariační analýza MeSH
- psychotické poruchy * diagnóza farmakoterapie MeSH
- schizofrenie * diagnóza farmakoterapie MeSH
- syndrom Nijmegen breakage * farmakoterapie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- antipsychotika * MeSH
BACKGROUND: Schizophrenia is associated with an increased risk of aggressive behaviour, which may partly be explained by illness-related changes in brain structure. However, previous studies have been limited by group-level analyses, small and selective samples of inpatients and long time lags between exposure and outcome. METHODS: This cross-sectional study pooled data from 20 sites participating in the international ENIGMA-Schizophrenia Working Group. Sites acquired T1-weighted and diffusion-weighted magnetic resonance imaging scans in a total of 2095 patients with schizophrenia and 2861 healthy controls. Measures of grey matter volume and white matter microstructural integrity were extracted from the scans using harmonised protocols. For each measure, normative modelling was used to calculate how much patients deviated (in z-scores) from healthy controls at the individual level. Ordinal regression models were used to estimate the associations of these deviations with concurrent aggressive behaviour (as odds ratios [ORs] with 99% confidence intervals [CIs]). Mediation analyses were performed for positive symptoms (i.e., delusions, hallucinations and disorganised thinking), impulse control and illness insight. Aggression and potential mediators were assessed with the Positive and Negative Syndrome Scale, Scale for the Assessment of Positive Symptoms or Brief Psychiatric Rating Scale. RESULTS: Aggressive behaviour was significantly associated with reductions in total cortical volume (OR [99% CI] = 0.88 [0.78, 0.98], p = .003) and global white matter integrity (OR [99% CI] = 0.72 [0.59, 0.88], p = 3.50 × 10-5) and additional reductions in dorsolateral prefrontal cortex volume (OR [99% CI] = 0.85 [0.74, 0.97], p =.002), inferior parietal lobule volume (OR [99% CI] = 0.76 [0.66, 0.87], p = 2.20 × 10-7) and internal capsule integrity (OR [99% CI] = 0.76 [0.63, 0.92], p = 2.90 × 10-4). Except for inferior parietal lobule volume, these associations were largely mediated by increased severity of positive symptoms and reduced impulse control. CONCLUSIONS: This study provides evidence that the co-occurrence of positive symptoms, poor impulse control and aggressive behaviour in schizophrenia has a neurobiological basis, which may inform the development of therapeutic interventions.
Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
- Klíčová slova
- ENIGMA, artificial intelligence, brain gray matter, schizophrenia, structural MRI, subtype,
- Publikační typ
- preprinty MeSH
BACKGROUND: The main aim of the present study is to determine the role of metabolites observed using proton magnetic resonance spectroscopy (1H-MRS) in obsessive-compulsive disorder (OCD). As the literature describing biochemical changes in OCD yields conflicting results, we focused on accurate metabolite quantification of total N-acetyl aspartate (tNAA), total creatine (tCr), total choline-containing compounds (tCh), and myo-inositol (mI) in the anterior cingulate cortex (ACC) to capture the small metabolic changes between OCD patients and controls and between OCD patients with and without medication. METHODS: In total 46 patients with OCD and 46 healthy controls (HC) matched for age and sex were included in the study. The severity of symptoms in the OCD was evaluated on the day of magnetic resonance imaging (MRI) using the Yale-Brown Obsessive-Compulsive Scale (YBOCS). Subjects underwent 1H-MRS from the pregenual ACC (pgACC) region to calculate concentrations of tNAA, tCr, tCho, and mI. Twenty-eight OCD and 28 HC subjects were included in the statistical analysis. We compared differences between groups for all selected metabolites and in OCD patients we analyzed the relationship between metabolite levels and symptom severity, medication status, age, and the duration of illness. RESULTS: Significant decreases in tCr (U = 253.00, p = 0.022) and mI (U = 197.00, p = 0.001) in the pgACC were observed in the OCD group. No statistically significant differences were found in tNAA and tCho levels; however, tCho revealed a trend towards lower concentrations in OCD patients (U = 278.00, p = 0.062). Metabolic concentrations showed no significant correlations with the age and duration of illness. The correlation statistics found a significant negative correlation between tCr levels and YBOCS compulsions subscale (cor = -0.380, p = 0.046). tCho and YBOCS compulsions subscale showed a trend towards a negative correlation (cor = -0.351, p = 0.067). Analysis of subgroups with or without medication showed no differences. CONCLUSIONS: Patients with OCD present metabolic disruption in the pgACC. The decrease in tCr shows an important relationship with OCD symptomatology. tCr as a marker of cerebral bioenergetics may also be considered as a biomarker of the severity of compulsions. The study failed to prove that metabolic changes correlate with the medication status or the duration of illness. It seems that a disruption in the balance between these metabolites and their transmission may play a role in the pathophysiology of OCD.
- Klíčová slova
- Choline-containing compounds, Creatine, Magnetic resonance spectroscopy, Myo-inositol, N-acetyl aspartate, Obsessive-compulsive disorder,
- MeSH
- cingulární gyrus diagnostické zobrazování metabolismus MeSH
- glutamin * metabolismus MeSH
- inositol metabolismus terapeutické užití MeSH
- kreatin metabolismus terapeutické užití MeSH
- kyselina aspartová metabolismus terapeutické užití MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- obsedantně kompulzivní porucha * diagnóza MeSH
- protonová magnetická rezonanční spektroskopie metody MeSH
- receptory antigenů T-buněk metabolismus terapeutické užití MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- glutamin * MeSH
- inositol MeSH
- kreatin MeSH
- kyselina aspartová MeSH
- receptory antigenů T-buněk MeSH
Despite the rising global burden of stroke and its socio-economic implications, the neuroimaging predictors of subsequent cognitive impairment are still poorly understood. We address this issue by studying the relationship of white matter integrity assessed within ten days after stroke and patients' cognitive status one year after the attack. Using diffusion-weighted imaging, we apply the Tract-Based Spatial Statistics analysis and construct individual structural connectivity matrices by employing deterministic tractography. We further quantify the graph-theoretical properties of individual networks. The Tract-Based Spatial Statistic did identify lower fractional anisotropy as a predictor of cognitive status, although this effect was mostly attributable to the age-related white matter integrity decline. We further observed the effect of age propagating into other levels of analysis. Specifically, in the structural connectivity approach we identified pairs of regions significantly correlated with clinical scales, namely memory, attention, and visuospatial functions. However, none of them persisted after the age correction. Finally, the graph-theoretical measures appeared to be more robust towards the effect of age, but still were not sensitive enough to capture a relationship with clinical scales. In conclusion, the effect of age is a dominant confounder especially in older cohorts, and unless appropriately addressed, may falsely drive the results of the predictive modelling.
- MeSH
- bílá hmota * diagnostické zobrazování MeSH
- cévní mozková příhoda * komplikace diagnostické zobrazování MeSH
- difuzní magnetická rezonance MeSH
- kognitivní dysfunkce * diagnostické zobrazování etiologie psychologie MeSH
- lidé MeSH
- senioři MeSH
- stárnutí MeSH
- zobrazování difuzních tenzorů metody MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
