Gray Matter Density Research Articles

Striatal dopamine gene network moderates the effect of early adversity on the risk for adult psychiatric and cardiometabolic comorbidity

Cardiometabolic and psychiatric disorders often co-exist and share common early life risk factors, such as low birth weight. However, the biological pathways linking early adversity to adult cardiometabolic/psychiatric comorbidity remain unknown. Dopamine (DA) neurotransmission in the striatum is sensitive to early adversity and influences the development of both cardiometabolic and psychiatric diseases. Here we show that a co-expression based polygenic score (ePGS) reflecting individual variations in the expression of the striatal dopamine transporter gene (SLC6A3) network significantly interacts with birth weight to predict psychiatric and cardiometabolic comorbidities in both adults (UK Biobank, N = 225,972) and adolescents (ALSPAC, N = 1188). Decreased birth weight is associated with an increased risk for psychiatric and cardiometabolic comorbidities, but the effect is dependent on a striatal SLC6A3 ePGS, that reflects individual variation in gene expression of genes coexpressed with the SLC6A3 gene in the striatum. Neuroanatomical analyses revealed that SNPs from the striatum SLC6A3 ePGS were significantly associated with prefrontal cortex gray matter density, suggesting a neuroanatomical basis for the link between early adversity and psychiatric and cardiometabolic comorbidity. Our study reveals that psychiatric and cardiometabolic diseases share common developmental pathways and underlying neurobiological mechanisms that includes dopamine signaling in the striatum.

Correlations between Cerebrospinal Fluid Biomarkers and Gray Matter Atrophy in Alzheimer's and Behavioural Variant Frontotemporal Dementia.

Distinguishing between frontotemporal dementia (FTD) and Alzheimer's disease (AD) in their early stages remains a significant clinical challenge. Cerebrospinal fluid (CSF) biomarkers (total Tau, phosphorylated Tau, and beta-amyloid) are promising candidates for identifying early differences between these conditions. This study investigates the relationship between grey matter density and CSF markers in the behavioural variant of frontotemporal dementia (bvFTD) and Alzheimer's disease (AD). CSF and 3D T1-weighted magnetic resonance (MR) images were acquired from 14 bvFTD patients, 15 AD patients, and 13 cognitively normal (CN) matched subjects. The CSF markers and their relative ratios (total Tau/beta-amyloid, phosphorylated Tau/beta-amyloid) were compared across the three groups. Voxel-based morphometry (VBM) was performed to characterize the anatomical changes in bvFTD and AD patients compared to CN subjects. Grey matter density maps were obtained by automatic segmentation of 3.0 Tesla 3D T1-Weighted MR Images, and their correlation with CSF markers and relative ratios was investigated. Results demonstrated that, as compared to CN subjects, AD patients are characterised by higher CSF total Tau levels and lower beta-amyloid levels; however, beta-amyloid and relative ratios discriminated AD from bvFTD. In addition, AD and bvFTD patients showed different patterns of atrophy, with AD exhibiting more central (temporal areas) and bvFTD more anterior (frontal areas) atrophy. A correlation was found between grey matter density maps and CSF marker concentrations in the AD group, with total Tau and phosphorylated Tau levels showing a high association with low grey matter density in the left superior temporal gyrus. The study concludes that while bvFTD lacks a CSF marker profile, CSF beta-amyloid levels are useful for differentiating AD from bvFTD. Furthermore, MR structural imaging can contribute significantly to distinguishing between the two pathologies.

Neural correlates of pain acceptance and the role of the cerebellum: Functional connectivity and anatomical differences in individuals with headaches versus matched controls.

Despite functional connectivity network dysfunction among individuals with headaches, no studies have examined functional connectivity neural correlates and anatomical differences in coping with headaches. This study investigated inter-individual variability in whole-brain functional connectivity and anatomical differences among 37 individuals with primary headaches and 24 age- and gender-matched controls, and neural correlates of psychological flexibility (PF) that was previously found to contribute to headache adjustment. Participants (84% women; M headache severity = 4/10; M age = 43 years) underwent functional magnetic resonance imaging scans and completed questionnaires to examine global and subnetwork brain areas, and their relations with PF components, controlling for age, gender, education, and head-motion. Seed and voxel-based contrast analyses between groups showed atypical functional connectivity of regions involved in pain matrix and core resting-state networks. Pain acceptance was the sole PF component that correlated with the cerebellum (x, y, z: 28, -72, -34, p-false discovery rate <0.001), where individuals with headaches showed higher grey matter density compared to controls. The cerebellum, recently implicated in modulating emotional and cognitive processes, was indicated to process information resembling what individuals do when practicing pain acceptance. Our findings establish for the first time this connection of the cerebellum and its role in pain acceptance. We propose that pain acceptance might be a behavioural biomarker target that could modulate problematic headache perceptions and brain networks abnormalities. This study highlights the potential use of emerging behavioural biomarkers in headache management, such as pain acceptance, and their role in modifying the headache experience. Notably, grey matter reorganization in the cerebellum and other known brain pain networks, could indicate brain networks that can be modified from targeted behavioural interventions to help decode the nociplastic mechanisms that predominates in headaches.

Association between Neural Plasticity and Pain-Related Fear in Chronic Ankle Instability: A Structural Neuroimaging Study.

Pain-related movement fear is a contributing factor to residual pain and functional deficits in chronic ankle instability (CAI), but its underlying neural mechanisms remain unclear. We aimed to (1) delineate whether participants with CAI exhibit discernible differences in specific emotion and pain-related brain regions, compared to a healthy control (HC) cohort and (2) explore potential neural mechanisms underlying pain and fear in participants with CAI, with an emphasis on investigating possible associations with pain-related neural plasticity. Cross-sectional study. University research laboratory. 28 participants with CAI (17males and 11 females; age: 31.28±6.31 years) and 28 HCs (16 males and 12 females; age: 30.18±7.59 years). We analyzed T1 structural imaging data from participants and assessed their fear of movement and pain intensity using the Tampa Scale for Kinesiophobia (TSK) and the Visual Analog Scale (VAS) for pain, respectively. We compared the mean gray matter (GM) density of pain-related area between the two groups and their correlations with the TSK and VAS scores. In comparison with the HC group, participants with CAI showed a significant decrease in the mean GM density in the prefrontal cortex (Cohen's d = -0.808) and periaqueductal gray (Cohen's d = -0.934). In participants with CAI, the mean GM density of the prefrontal cortex (PFC) was negatively correlated with the TSK scores (r = -0.531). During intense exercise, the mean GM density of the periaqueductal gray (PAG) was negatively correlated with the VAS scores (r = -0.484). Additionally, TSK scores were positively correlated with VAS scores (r = 0.455). Our exploratory findings suggest that, in participants with CAI, the atrophy of the PFC and PAG may be associated with pain-related fear. Future clinical diagnosis and treatment for CAI should consider the impact of psychological barriers on functional recovery.

A structural MRI marker predicts individual differences in impulsivity and classifies patients with behavioral-variant frontotemporal dementia from matched controls.

Impulsivity and higher preference for sooner over later rewards (i.e., delay discounting) are transdiagnostic markers of many psychiatric and neurodegenerative disorders. Yet, their neurobiological basis is still debated. Here, we aimed at 1) identifying a structural MRI signature of delay discounting in healthy adults, and 2) validating it in patients with behavioral variant frontotemporal dementia (bvFTD)-a neurodegenerative disease characterized by high impulsivity. We used a machine-learning algorithm to predict individual differences in delay discounting rates based on whole-brain grey matter density maps in healthy male adults (Study 1, N=117). This resulted in a cross-validated prediction-outcome correlation of r=0.35 (p=0.0028). We tested the validity of this brain signature in an independent sample of 166 healthy adults (Study 2) and its clinical relevance in 24 bvFTD patients and 18 matched controls (Study 3). In Study 2, responses of the brain signature did not correlate significantly with discounting rates, but in both Studies 1 and 2, they correlated with psychometric measures of trait urgency-a measure of impulsivity. In Study 3, brain-based predictions correlated with discounting rates, separated bvFTD patients from controls with 81% accuracy, and were associated with the severity of disinhibition among patients. Our results suggest a new structural brain pattern-the Structural Impulsivity Signature (SIS)-which predicts individual differences in impulsivity from whole-brain structure, albeit with small-to-moderate effect sizes. It provides a new brain target that can be tested in future studies to assess its diagnostic value in bvFTD and other neurodegenerative and psychiatric conditions characterized by high impulsivity.

Comprehensive MRI assessment reveals subtle brain findings in non-hospitalized post-COVID patients with cognitive impairment.

Impaired cognitive ability is one of the most frequently reported neuropsychiatric symptoms in the post-COVID phase among patients. It is unclear whether this condition is related to structural or functional brain changes. In this study, we present a multimodal magnetic resonance imaging study of 36 post-COVID patients and 36 individually matched controls who had a mild form of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) infection from March 2020 to February 2022. This study aimed to investigate structural and functional brain alterations and their correlation with post-COVID symptoms and neurocognitive functions. The study protocol comprised an assessment of physical fatigue [Fatigue Severity Scale (FSS)], mental fatigue (Mental Fatigue Scale (MFS)], depression [Montgomery Asberg Depression Rating Scale (MADRS)], anxiety [Hospital Anxiety and Depression Scale (HAD)], post-COVID Symptoms Severity Score, and neurocognitive status [Repeatable Battery for the Assessment of Neuropsychological Status Update (RBANS)]. The magnetic resonance imaging protocol included morphological sequences, arterial spin labeling (ASL) and dynamic susceptibility contrast-enhanced (DSC) perfusion, diffusion tensor imaging (DTI), and resting-state functional magnetic resonance imaging (fMRI) sequences. Using these protocols, the assessments of macrostructural abnormalities, perfusion, gray matter density, white matter integrity, and brain connectivity were performed. Post-COVID patients had higher levels of physical fatigue, mental fatigue, depression, and anxiety than controls and showed cognitive impairment in all the RBANS domains except in Visuospatial/Construction. The subjective mental fatigue correlated with objective impaired cognitive ability in the RBANS test, particularly in the Attention domain. There were no differences between patients and controls regarding macrostructural abnormalities, regional volumes, regional perfusion metrics, gray matter density, or DTI parameters. We observed a significant positive correlation between RBANS Total Scale Index score and gray matter volume in the right superior/middle-temporal gyrus (p < 0.05) and a significant negative correlation between the white matter integrity and post-COVID symptoms (p < 0.05) in the same area. The connectivity differences were observed between patients and controls in a few regions, including the right middle frontal gyrus, an important area of convergence of the dorsal and ventral attention networks. We also noted a positive correlation between post-COVID symptoms and increased connectivity in the right temporoparietal junction, which is part of the ventral attention system. In non-hospitalized subjects with post-COVID, we did not find any structural brain changes or changes in perfusion, compared to controls. However, we noted differences in connectivity within an important area for attention processes, which may be associated with post-COVID brain fog.

Differences in Grey Matter Concentrations and Functional Connectivity between Young Carriers and Non-Carriers of the APOE ε4 Genotype.

Background: The pathophysiology of Alzheimer's disease (AD) may begin developing years or even decades prior to the manifestation of its first symptoms. The APOE ε4 genotype is a prominent genetic risk for AD that has been found to be associated with brain changes across the lifespan since early adulthood. Thus, studying brain changes that may occur in young adults with an APOE ε4 status is highly relevant. Objective: Examine potential differences in grey matter (GM) and functional connectivity (FC) in brains of cognitively healthy young APOE ε4 carriers and non-carriers, denoted here as ε4(+) and ε4(-), respectively. Methods: Three Tesla magnetic resonance imaging (MRI) brain scans were acquired from cognitively healthy young participants aged approximately 20 years (n = 151). Voxel-based morphometry (VBM) analysis was employed to identify potential structural differences in GM between ε4(+) and ε4(-). In a subsequent seed-based connectivity (SBC) analysis, brain regions that structurally differed in the VBM analysis were considered as seeds and correlated with all the remaining voxels across the brains to then measure the differences in FC between groups. Results: The VBM analysis suggested that ε4(+) (n = 28) had greater GM densities relative to ε4(-) (n = 123) in the left hippocampus and the left posterior insula (puncorr < 0.001). However, the effect did not survive the correction for multiple comparisons, suggesting minimal structural differences in this age range. In contrast, the SBC analysis indicated that ε4(+) exhibited significantly decreased FC between the left hippocampus and areas of the left middle temporal gyrus (n = 27) compared to ε4(-) (n = 102). These results remained significant after multiple comparisons (pFDR < 0.05). Lastly, no statistically significant differences in FC between groups were observed for the left insular seed (pFDR > 0.05). Discussion: These results suggest early structural and functional brain changes associated with the APOE ε4 genotype on young adults. Yet, they must be cautiously interpreted and contrasted with both older adults with genetic risk for AD and patients diagnosed with AD.

Sustained improvements in brain health and metabolic markers 24 months following bariatric surgery.

Obesity and its metabolic complications are associated with lower grey matter and white matter densities, whereas weight loss after bariatric surgery leads to an increase in both measures. These increases in grey and white matter density are significantly associated with post-operative weight loss and improvement of the metabolic/inflammatory profiles. While our recent studies demonstrated widespread increases in white matter density 4 and 12 months after bariatric surgery, it is not clear if these changes persist over time. The underlying mechanisms also remain unknown. In this regard, numerous studies demonstrate that the enlargement or hypertrophy of mature adipocytes, particularly in the visceral fat compartment, is an important marker of adipose tissue dysfunction and obesity-related cardiometabolic abnormalities. We aimed (i) to assess whether the increases in grey and white matter densities previously observed at 12 months are maintained 24 months after bariatric surgery; (ii) to examine the association between these structural brain changes and adiposity and metabolic markers 24 months after bariatric surgery; and (iii) to examine the association between abdominal adipocyte diameter at the time of surgery and post-surgery grey and white matter densities changes. Thirty-three participants undergoing bariatric surgery were recruited. Grey and white matter densities were assessed from T1-weighted magnetic resonance imaging scans acquired prior to and 4, 12 and 24 months post-surgery using voxel-based morphometry. Omental and subcutaneous adipose tissue samples were collected during the surgical procedure. Omental and subcutaneous adipocyte diameters were measured by microscopy of fixed adipose tissue samples. Linear mixed-effects models were performed controlling for age, sex, surgery type, initial body mass index, and initial diabetic status. The average weight loss at 24 months was 33.6 ± 7.6%. A widespread increase in white matter density was observed 24 months post-surgery mainly in the cerebellum, brainstem and corpus callosum (P < 0.05, false discovery rate) as well as some regions in grey matter density. Greater omental adipocyte diameter at the time of surgery was associated with greater changes in total white matter density at 24 months (P = 0.008). A positive trend was observed between subcutaneous adipocyte diameter at the time of surgery and changes in total white matter density at 24 months (P = 0.05). Our results show prolonged increases in grey and white matter densities up to 24 months post-bariatric surgery. Greater preoperative omental adipocyte diameter is associated with greater increases in white matter density at 24 months, suggesting that individuals with excess visceral adiposity might benefit the most from surgery.

Integrating stereotypes and factual evidence in interpersonal communication

Stereotypes can exert a powerful influence on our interactions with others, potentially leading to prejudice when factual evidence is ignored. Here, we identify neuroanatomical and developmental factors that influence the real-time integration of stereotypes and factual evidence during live social interactions. The study uses precisely quantified communicative exchanges in a longitudinal cohort of seventeen-year-olds followed since infancy, testing their ability to moderate stereotype tendencies toward children as contrary evidence accumulates. Our results indicate that the impact of stereotypes on communicative behavior is linked to individual variations in gray matter density and cortical thickness in the right anterior cingulate gyrus. In contrast, the ability to moderate stereotype tendencies is influenced by developmental exposure to social interactions during the initial years of life, beyond the effects of familial environment and later experiences. These findings pinpoint a key brain structure underlying stereotype tendencies and suggest that early-life social experiences have lasting consequences on how individuals integrate factual evidence in interpersonal communication.

Gene expression and brain imaging association study reveals gene signatures in major depressive disorder.

Major depressive disorder is often characterized by changes in the structure and function of the brain, which are influenced by modifications in gene expression profiles. How the depression-related genes work together within the scope of time and space to cause pathological changes remains unclear. By integrating the brain-wide gene expression data and imaging data in major depressive disorder, we identified gene signatures of major depressive disorder and explored their temporal-spatial expression specificity, network properties, function annotations and sex differences systematically. Based on correlation analysis with permutation testing, we found 345 depression-related genes significantly correlated with functional and structural alteration of brain images in major depressive disorder and separated them by directional effects. The genes with negative effect for grey matter density and positive effect for functional indices are enriched in downregulated genes in the post-mortem brain samples of patients with depression and risk genes identified by genome-wide association studies than genes with positive effect for grey matter density and negative effect for functional indices and control genes, confirming their potential association with major depressive disorder. By introducing a parameter of dispersion measure on the gene expression data of developing human brains, we revealed higher spatial specificity and lower temporal specificity of depression-related genes than control genes. Meanwhile, we found depression-related genes tend to be more highly expressed in females than males, which may contribute to the difference in incidence rate between male and female patients. In general, we found the genes with negative effect have lower network degree, more specialized function, higher spatial specificity, lower temporal specificity and more sex differences than genes with positive effect, indicating they may play different roles in the occurrence and development of major depressive disorder. These findings can enhance the understanding of molecular mechanisms underlying major depressive disorder and help develop tailored diagnostic and treatment strategies for patients of depression of different sex.

Age-related alterations in human cortical microstructure across the lifespan: Insights from high-gradient diffusion MRI.

The human brain undergoes age-related microstructural alterations across the lifespan. Soma and Neurite Density Imaging (SANDI), a novel biophysical model of diffusion MRI, provides estimates of cell body (soma) radius and density, and neurite density in gray matter. The goal of this cross-sectional study was to assess the sensitivity of high-gradient diffusion MRI toward age-related alterations in cortical microstructure across the adult lifespan using SANDI. Seventy-two cognitively unimpaired healthy subjects (ages 19-85 years; 40 females) were scanned on the 3T Connectome MRI scanner with a maximum gradient strength of 300mT/m using a multi-shell diffusion MRI protocol incorporating 8 b-values and diffusion time of 19 ms. Intra-soma signal fraction obtained from SANDI model-fitting to the data was strongly correlated with age in all major cortical lobes (r = -0.69 to -0.60, FDR-p < 0.001). Intra-soma signal fraction (r = 0.48-0.63, FDR-p < 0.001) and soma radius (r = 0.28-0.40, FDR-p < 0.04) were significantly correlated with cortical volume in the prefrontal cortex, frontal, parietal, and temporal lobes. The strength of the relationship between SANDI metrics and age was greater than or comparable to the relationship between cortical volume and age across the cortical regions, particularly in the occipital lobe and anterior cingulate gyrus. In contrast to the SANDI metrics, all associations between diffusion tensor imaging (DTI) and diffusion kurtosis imaging metrics and age were low to moderate. These results suggest that high-gradient diffusion MRI may be more sensitive to underlying substrates of neurodegeneration in the aging brain than DTI and traditional macroscopic measures of neurodegeneration such as cortical volume and thickness.

MRI evidence of gray matter loss in COVID-19 patients with cognitive and olfactory disorders.

The aim of this study was to assess COVID-19-related gray matter (GM) structural alterations in two distinct groups of patients presenting with the prevailing and distinctive COVID-19-related neurological symptoms - isolated olfactory disorders as sole neurological manifestation (COVID-OD) and cognitive disorders (COVID-CD) - as compared to a control group of unaffected individuals. The study included 61 COVID-CD patients (57 [60-63] years, 62% females), 84 COVID-OD patients (49 [35-57] years, 60% females), and 17 controls (51 [41-52] years, 41% females). Region-based morphometry (RBM) and voxel-based morphometry (VBM) were performed on T1-weighted MRI scans to assess GM regional volume and voxel-wise density differences between COVID-19 patients and controls. Surface-based morphometry (SBM) was applied to investigate cortical thickness alterations. The statistical models built to assess GM structural differences among groups included total intracranial volume and age as nuisance variables. The multi-morphometric analysis revealed statistically significant (p < 0.05 corrected for multiple comparisons) reduction in GM regional volumes, in voxel-wise GM density and in cortical thickness in both COVID-CD and COVID-OD patient groups as compared to controls. Across all three analyses, COVID-CD patients showed more distributed and severe GM loss than COVID-OD patients. The most prominently affected GM regions in the COVID-CD group included the hippocampus, putamen, cingulate gyrus, precuneus, precentral and postcentral gyri, amygdala, lingual gyrus, and caudate nucleus. Our MRI findings show that COVID-19-related olfactory and cognitive disorders both induce GM atrophy, although at different degrees of severity, likely indicative of neurodegeneration and neuroinflammation.

Cholinergic nucleus degeneration and its association with gait impairment in Parkinson’s disease

BackgroundThe contribution of cholinergic degeneration to gait disturbance in Parkinson’s disease (PD) is increasingly recognized, yet its relationship with dopaminergic-resistant gait parameters has been poorly investigated. We investigated the association between comprehensive gait parameters and cholinergic nucleus degeneration in PD.MethodsThis cross-sectional study enrolled 84 PD patients and 69 controls. All subjects underwent brain structural magnetic resonance imaging to assess the gray matter density (GMD) and volume (GMV) of the cholinergic nuclei (Ch123/Ch4). Gait parameters under single-task (ST) and dual-task (DT) walking tests were acquired using sensor wearables in PD group. We compared cholinergic nucleus morphology and gait performance between groups and examined their association.ResultsPD patients exhibited significantly decreased GMD and GMV of the left Ch4 compared to controls after reaching HY stage > 2. Significant correlations were observed between multiple gait parameters and bilateral Ch123/Ch4. After multiple testing correction, the Ch123/Ch4 degeneration was significantly associated with shorter stride length, lower gait velocity, longer stance phase, smaller ankle toe-off and heel-strike angles under both ST and DT condition. For PD patients with HY stage 1–2, there were no significant degeneration of Ch123/4, and only right side Ch123/Ch4 were corrected with the gait parameters. However, as the disease progressed to HY stage > 2, bilateral Ch123/Ch4 nuclei showed correlations with gait performance, with more extensive significant correlations were observed in the right side.ConclusionsOur study demonstrated the progressive association between cholinergic nuclei degeneration and gait impairment across different stages of PD, and highlighting the potential lateralization of the cholinergic nuclei’s impact on gait impairment. These findings offer insights for the design and implementation of future clinical trials investigating cholinergic treatments as a promising approach to address gait impairments in PD.

Enduring maternal brain changes and their role in mediating motherhood’s impact on well-being

Parenthood, particularly motherhood, is known to impact the structure and function of the brain in the short term, but the long-term effects of parenthood and their impacts on well-being are still poorly understood. This study explores the potential longer-term associations between parenthood and the brain, parenthood and well-being, and the potential role of brain modifications in influencing mothers’ well-being. Using data from the UK Biobank, which includes brain imaging information from individuals aged 45–82 at the MRI scanning, we discovered differences in brain structure between mothers and non-mothers, with mothers exhibiting widely distributed higher gray matter density, particularly strong in frontal and occipital regions. No brain changes were observed in fathers. Parents reported a higher sense of life’s meaning compared to their childless counterparts. Gray matter changes did not mediate the relationship between motherhood and well-being. This suggests that the alterations in gray matter associated with motherhood do not play a deterministic role in shaping long-term changes in well-being.

Linking functional and structural brain organisation with behaviour in healthy adults.

Multimodal data integration approaches, such as Linked Independent Component Analysis (LICA), increase sensitivity to brain-behaviour relationships and allow us to probe the relationship between modalities. Here we focus on inter-regional functional and structural organisation to determine if organisational patterns persist across modalities and if investigating multi-modality organisations provides increased sensitivity to brain-behaviour associations. We utilised multimodal magnetic resonance imaging (MRI; T1w, resting-state functional [fMRI] and diffusion weighted [DWI]) and behavioural data from the Human Connectome Project (HCP, n=676; 51% female). Unimodal features were extracted to produce individual grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps from the T1w, DWI and fMRI data, respectively. DWI and fMRI analyses were restricted to subcortical regions for computational reasons. LICA was then used to integrate features, generating 100 novel independent components. Associations between these components and demographic/behavioural (n=308) variables were examined. 15 components were significantly associated with various demographic/behavioural measures. 2 components were strongly related to various measures of intoxication, driven by DWI and resemble components previously identified. Another component was driven by striatal functional data and related to working memory. A small number of components showed shared variance between structure and function but none of these displayed any significant behavioural associations. Our working memory findings provide support for the use of fMRI connectopic mapping in future research of working memory. Given the lack of behaviourally relevant shared variance between functional and structural organisation, as indexed here, we question the utility of integrating connectopic maps and tractography data.

Effects of gender-affirming hormone therapy on gray matter density, microstructure and monoamine oxidase A levels in transgender subjects

MAO-A catalyzes the oxidative degradation of monoamines and is thus implicated in sex-specific neuroplastic processes that influence gray matter (GM) density (GMD) and microstructure (GMM). Given the exact monitoring of plasma hormone levels and sex steroid intake, transgender individuals undergoing gender-affirming hormone therapy (GHT) represent a valuable cohort to potentially investigate sex steroid-induced changes of GM and concomitant MAO-A density. Here, we investigated the effects of GHT over a median time period of 4.5 months on GMD and GMM as well as MAO-A distribution volume. To this end, 20 cisgender women, 11 cisgender men, 20 transgender women and 10 transgender men underwent two MRI scans in a longitudinal design. PET scans using [11C]harmine were performed before each MRI session in a subset of 35 individuals. GM changes determined by diffusion weighted imaging (DWI) metrics for GMM and voxel based morphometry (VBM) for GMD were estimated using repeated measures ANOVA. Regions showing significant changes of both GMM and GMD were used for the subsequent analysis of MAO-A density. These involved the fusiform gyrus, rolandic operculum, inferior occipital cortex, middle and anterior cingulum, bilateral insula, cerebellum and the lingual gyrus (post-hoc tests: pFWE+Bonferroni < 0.025). In terms of MAO-A distribution volume, no significant effects were found. Additionally, the sexual desire inventory (SDI) was applied to assess GHT-induced changes in sexual desire, showing an increase of SDI scores among transgender men. Changes in the GMD of the bilateral insula showed a moderate correlation to SDI scores (rho = - 0.62, pBonferroni = 0.047). The present results are indicative of a reliable influence of gender-affirming hormone therapy on 1) GMD and GMM following an interregional pattern and 2) sexual desire specifically among transgender men.

Changes in primary visual and auditory cortex of blind and sighted adults following 10weeks of click-based echolocation training.

Recent work suggests that the adult human brain is very adaptable when it comes to sensory processing. In this context, it has also been suggested that structural "blueprints" may fundamentally constrain neuroplastic change, e.g. in response to sensory deprivation. Here, we trained 12 blind participants and 14 sighted participants in echolocation over a 10-week period, and used MRI in a pre-post design to measure functional and structural brain changes. We found that blind participants and sighted participants together showed a training-induced increase in activation in left and right V1 in response to echoes, a finding difficult to reconcile with the view that sensory cortex is strictly organized by modality. Further, blind participants and sighted participants showed a training induced increase in activation in right A1 in response to sounds per se (i.e. not echo-specific), and this was accompanied by an increase in gray matter density in right A1 in blind participants and in adjacent acoustic areas in sighted participants. The similarity in functional results between sighted participants and blind participants is consistent with the idea that reorganization may be governed by similar principles in the two groups, yet our structural analyses also showed differences between the groups suggesting that a more nuanced view may be required.

Magnetic Resonance Imaging in the Study of Catatonia: Use of DWI and Resting State fMRI

Background: catatonia is the focus of neurophysiological research as a syndrome with unspecified pathogenesis. Modern neuroimaging techniques contribute to the understanding of the pathophysiological mechanisms of this disorder. The aim was to conduct a systematic review of the scientific literature to confirm that catatonia is associated with structural and functional changes in the brain. The analysis made up researches using diffusion MRI for judgement on indirect measure of changes in white or gray matter density using a fractional anisotropy (FA) and resting state functional MRI for assessment a measure of connectivity. Materials and methods: PubMed, ScienceDirect and Mendeley databases were searched using the search terms (and their derivatives) for: “catatonia”, “resting state functional magnetic resonance imaging” and “catatonia”, “diffusion weighted magnetic resonance imaging”. The search yielded 147 publications for preliminary screening, of which 96 were on fMRI of catatonia and 51 on dMRI. During the screening stage, duplicates and articles that could not be accessed were removed. This left 21 fMRI articles and 18 dMRI articles. After which the articles were checked for compliance with the inclusion criteria: 1) original full-text articles; 2) identification of catatonia not caused by a somatic disease and verified using the Bush–Francis and/or Northoff psychometric scales; 3) age of the examined 18 years and over. 3 fMRI and 3 dMRI articles were included. Conclusions: aberrations of FA indicators were found in catatonia, which may be associated with the density of the white matter of the brain. Changes in connectivity in the somatosensory network have been identified, which allows to consider these disorders as potential markers of catatonia. To confirm the hypothesis and results obtained, further research is required due to the small number of publications on this topic.

Unsupervised multimodal modeling of cognitive and brain health trajectories for early dementia prediction

Predicting the course of neurodegenerative disorders early has potential to greatly improve clinical management and patient outcomes. A key challenge for early prediction in real-world clinical settings is the lack of labeled data (i.e., clinical diagnosis). In contrast to supervised classification approaches that require labeled data, we propose an unsupervised multimodal trajectory modeling (MTM) approach based on a mixture of state space models that captures changes in longitudinal data (i.e., trajectories) and stratifies individuals without using clinical diagnosis for model training. MTM learns the relationship between states comprising expensive, invasive biomarkers (β-amyloid, grey matter density) and readily obtainable cognitive observations. MTM training on trajectories stratifies individuals into clinically meaningful clusters more reliably than MTM training on baseline data alone and is robust to missing data (i.e., cognitive data alone or single assessments). Extracting an individualized cognitive health index (i.e., MTM-derived cluster membership index) allows us to predict progression to AD more precisely than standard clinical assessments (i.e., cognitive tests or MRI scans alone). Importantly, MTM generalizes successfully from research cohort to real-world clinical data from memory clinic patients with missing data, enhancing the clinical utility of our approach. Thus, our multimodal trajectory modeling approach provides a cost-effective and non-invasive tool for early dementia prediction without labeled data (i.e., clinical diagnosis) with strong potential for translation to clinical practice.

Multimodal workflows optimally predict response to repetitive transcranial magnetic stimulation in patients with schizophrenia: a multisite machine learning analysis

The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial. The models incorporated pre-treatment sMRI, clinical, sociodemographic, and polygenic risk score (PRS) data. Patients were randomly assigned to receive active (N = 45) or sham (N = 47) rTMS treatment. The prediction target was individual response, defined as ≥20% reduction in pre-treatment negative symptom sum scores of the Positive and Negative Syndrome Scale. Our multimodal sequential prediction workflow achieved a balanced accuracy (BAC) of 94% (non-responders: 92%, responders: 95%) in the active-treated group and 50% in the sham-treated group. The clinical, clinical + PRS, and sMRI-based classifiers yielded BACs of 65%, 76%, and 80%, respectively. Apparent sadness, inability to feel, educational attainment PRS, and unemployment were most predictive of non-response in the clinical + PRS model, while grey matter density reductions in the default mode, limbic networks, and the cerebellum were most predictive in the sMRI model. Our sequential modelling approach provided superior predictive performance while minimising the diagnostic burden in the clinical setting. Predictive patterns suggest that rTMS responders may have higher levels of brain grey matter in the default mode and salience networks which increases their likelihood of profiting from plasticity-inducing brain stimulation methods, such as rTMS. The future clinical implementation of our models requires findings to be replicated at the international scale using stratified clinical trial designs.