Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies

Transdiagnostic relationships between childhood adversity and cortical thickness of the rostral anterior cingulate cortex

Childhood adversity (CA) is the leading preventable risk factor for mental illness. While CA can exacerbate affective symptoms across various psychiatric disorders, its impact on brain morphology, particularly the rostral anterior cingulate cortex (rACC), has mainly been studied in specific stress-related psychiatric disorders, such as depression and anxiety disorders. Therefore, we set out to disentangle the relationships between CA, psychopathology and brain structure across a broader range of psychiatric disorders. We studied 227 patients with stress-related and/or neurodevelopmental disorders and 95 healthy controls. We focused on the rACC, as this region is highly impacted by CA and has a pivotal role in affective functions across psychiatric disorders. The presence of CA was associated with decreased left rACC thickness across the whole sample, independent of psychopathology. Additionally, the contralateral right rACC was associated with psychopathology, with psychiatric patients having a thinner rACC compared to healthy controls, which was most pronounced in the stress-related disorders group. While left rACC thickness negatively correlated with social anxiety-related concerns, right rACC thickness negatively correlated with various core symptoms of stress-related and neurodevelopmental disorders. Finally, our exploratory analyses across cortical regions did not reveal any robust effects that survived multiple comparison correction. Taken together, our results suggest that within the stress-related disorders group, the CA-related thinning of the left rACC may compound the effects of the affected right rACC. This 'double hit' in stress-related disorders may contribute to the well-established phenomenon that CA leads to a worse illness trajectory in these disorders.

Hemispheric asymmetry in language-related brain regions

Structural asymmetries of the human brain have been widely studied in previous research. However, there is a lack of consistency across studies in terms of whether brain regions are larger in the left hemisphere than the right (leftward asymmetry), larger in the right hemisphere than the left (rightward asymmetry), or similar in both hemispheres (no asymmetry). Moreover, some of the existing studies exploring brain asymmetry were based on only small sample sizes and/or restricted to younger participants. Thus, here we analysed brain asymmetry in a well-powered sample (n = 532) later in life (mean age: 67 years). Given that language is known to be strongly lateralized in the brain, the current study focused on regions related to language. When assessing cortical volumes and surface areas, we observed significant leftward asymmetries for the superior temporal gyrus, superior temporal sulcus, supramarginal gyrus, pars opercularis, transverse gyrus, and temporal gyrus, whereas the pars triangularis showed a significant rightward asymmetry. In contrast, when assessing cortical thickness, we detected a significant leftward asymmetry for the pars triangularis and a significant rightward asymmetry for the superior temporal sulcus. The present observations on asymmetry in language-related brain regions in a large sample of older but neurologically healthy participants may serve as a normative framework against which data from clinical samples can be compared.

Accuracy of Boltless Frame-Based Stereo-Electroencephalography Electrode Implantation

BACKGROUND AND OBJECTIVES

Boltless implantation of stereo-electroencephalography electrode is a useful alternative especially when anchor bolt is not available such as in country with limited resources or is less appropriate such as placement in patients with thin skull or at the occiput area, despite some drawbacks including potential dislodgement. While the accuracy of implantation using anchor bolt is well-studied, data on boltless implantation remain scarce. This study aimed to reveal the accuracy, permissible error for actual placement of electrodes within the grey matter, and delayed electrode dislodgement in boltless implantation.

METHODS

A total of 120 electrodes were implanted in 15 patients using a Leksell Stereotactic G Frame with each electrode fixed on the scalp using sutures. Target point error was defined as the Euclidean distance between the planned target and the electrode tip on immediate postimplantation computed tomography. Similarly, delayed dislodgement was defined as the Euclidean distance between the electrode tips on immediate postimplantation computed tomography and delayed MRI. The factors affecting accuracy were evaluated using multiple linear regression. The permissible error was defined as the largest target point error that allows the maximum number of planned gray matter electrode contacts to be actually placed within the gray matter as intended.

RESULTS

The median (IQR) target point error was 2.6 (1.7-3.5) mm, and the permissible error was 3.2 mm. The delayed dislodgement, with a median (IQR) of 2.2 (1.4-3.3) mm, was dependent on temporal muscle penetration ( P = 5.0 × 10 -4 ), scalp thickness ( P < 5.1 × 10 -3 ), and insertion angle ( P = 3.4 × 10 -3 ).

CONCLUSION

Boltless implantation of stereo-electroencephalography electrode offers an accuracy comparable to those using anchor bolt. During the planning of boltless implantation, target points should be placed within 3.2 mm from the gray-white matter junction and a possible delayed dislodgement of 2.2 mm should be considered.

Quantitative magnetization transfer and g-ratio imaging of white matter myelin in early psychotic spectrum disorders

Myelin abnormalities in white matter have been implicated in the pathophysiology of psychotic spectrum disorders (PSD), which are characterized by brain dysconnectivity as a core feature. Among evidence from in vivo MRI studies, diffusion imaging findings have largely supported disrupted white matter integrity in PSD; however, they are not specific to myelin changes. Using a multimodal imaging approach, the current study aimed to further delineate myelin and microstructural changes in the white matter of a young PSD cohort. We utilized quantitative magnetization transfer (qMT) imaging combined with advanced diffusion imaging to estimate specific myelin-related biophysical properties in 51 young adult PSD patients compared with 38 age-matched healthy controls. The macromolecular proton fraction (MPF) obtained from qMT was used as a specific marker of myelin content. Additionally, MPF was employed along with diffusion metrics of axonal density (vic) and extra-cellular volume fraction to derive the g-ratio, a measure of relative myelin sheath thickness defined as the ratio of inner to outer axonal diameter. Compared to controls, we observed a widespread MPF reduction and localized g-ratio increase in patients, primarily those with a diagnosis of schizophrenia or depressive schizoaffective disorder. No between-group differences were noted in vic, suggesting similar axonal densities across groups. Correlation analysis revealed that lower MPF was significantly related to poorer working memory performance in PSD, while the HC group showed a positive association for working memory with both g-ratio and vic. The pattern of changes observed in our multimodal imaging markers suggests that PSD, depending on symptomatology, is characterized by specific alterations in white matter integrity and myelin-axonal geometry of major white matter tracts, which may impact working memory function. These findings provide a more detailed view of myelin-related white matter changes in early stages of PSD.

Depicting Coupling Between Cortical Morphology and Functional Networks in Major Depressive Disorder

An enduring mystery in neuroscience is the intricate interplay between brain anatomical structure and functional dynamics, particularly in the context of mental disorders such as major depressive disorder (MDD). A pivotal scientific question arises: How does the cortical morphology-function coupling (MFC) manifest in MDD, and what insights can this coupling provide into the clinical manifestations of the disorder? To tackle this question, we conducted a comprehensive analysis using high-resolution T1-weighted structural magnetic resonance imaging (MRI) and resting-state functional MRI (rs-fMRI) data from a cohort of 830 MDD patients and 853 healthy control (HC). By constructing morphological and functional networks based on cortical gray matter (GM) morphology and regional rs-fMRI time series correlations, respectively, we aimed to quantify MFC by assessing the spatial correspondence between these networks. Results revealed that MDD patients exhibited a spatial hierarchical pattern of MFC similar to HC, with variations in specific networks. Specifically, lower coupling was observed in the visual network (VIS) and sensorimotor network (SMN), while higher coupling was noted in the default mode network (DMN) and frontoparietal network (FPN). Notably, MDD patients demonstrated significantly increased MFC within the VIS, SMN, and dorsal attention network (DAN) compared to HC. Furthermore, altered MFC in the VIS correlated positively with depressive symptom severity. These findings contribute to our understanding of the potential clinical significance of MFC alterations in MDD.

Structural brain alterations and clinical associations in individuals with chronic nonspecific neck pain

BACKGROUND

Chronic pain is associated with changes in brain structures. However, the specific morphological changes in chronic nonspecific neck pain (CNSNP) are still unclear.

OBJECTIVES

To investigate altered brain morphology in patients with CNSNP and its relationships with clinical characteristics of neck pain.

DESIGN

Cross-sectional study.

METHODS

Thirty CNSNP and 30 controls underwent T1-weighted structural MRI to assess whole-brain vertex-wise cortical thickness and gray matter volume. Between-group differences were determined using cluster-wise correction for multiple comparisons and analyses of global structure and pain-related regions of interest (ROIs). Pain outcomes were neck pain duration, intensity, disability and pressure pain thresholds (PPTs) over the cervical spine.

RESULTS

Overall, the cluster-wise analysis revealed increased cortical thickness and decreased gray matter volume in several brain regions such as the precuneus, supramarginal gyrus and parietal cortex in the neck pain group (CWP<0.05). The global analysis showed that the neck pain group had increased total thickness and decreased total volume (p < 0.05). The ROI analysis showed that the neck pain group exhibited increased thickness in the primary somatosensory cortex (S1), anterior cingulate cortex (ACC) and precuneus and decreased volume in the prefrontal cortex (PFC), S1, ACC and insula compared to controls (adjusted p-values<0.05). Reduced insula volume correlated with greater neck disability (r = -0.53, adjusted p-value<0.01). Increased PPTs correlated with greater S1 and precuneus thickness (r = 0.46-0.48, adjusted p-values<0.05) and S1 volume (r = 0.53-0.58, adjusted p-values<0.05).

CONCLUSION

Patients with CNSNP exhibited increased cortical thickness and decreased gray matter volume in brain regions involved in pain processing and emotional and cognitive responses.

Changes of brain structure and structural covariance networks in Parkinson's disease with different sides of onset

Background

Parkinson's disease (PD) typically presents with unilateral symptoms in early stages, starting on one side and progressing, with the onset side showing more severe motor symptoms even after bilateralization. This asymmetry may reflect complex interactions among multiple brain regions and their network connections. In this study, we aimed to use surface-based morphometry (SBM) and structural covariance networks (SCNs) to investigate the differences in brain structure and network characteristics between patients with left-onset PD (LPD) and right-onset PD (RPD).

Methods

A total of 51 LPD and 49 RPD patients were recruited. Clinical assessments included the Unified Parkinson's Disease Rating Scale motor section, Hoehn and Yahr stage, Mini-Mental State Examination, Parkinson's Disease Questionnaire, and Beck Depression Inventory. All participants underwent 3 T structural MRI. FreeSurfer was used to perform vertex-wise comparisons of cortical surface area (CSA) and cortical thickness (CT), whereas the Brain Connectivity Toolbox was implemented to construct and analyze the structural covariance networks.

Results

In patients with LPD, we found reduced CSA in the right supramarginal gyrus (SMG), right precuneus (PCUN), left inferior parietal lobule (IPL), and left lingual gyrus (LING) compared to RPD, while no significant differences in CT were found between the two groups. The CSA of the right PCUN showed a significant positive correlation with MMSE score in LPD patients. In our SCNs analysis, LPD patients exhibited increased normalized characteristic path length and decreased small-world index in CSA-based networks, while in CT-based networks, they showed increased small-world index and global efficiency compared to RPD. No significant differences in nodal characteristics were observed in either CSA-based or CT-based networks between the two groups.

Conclusion

In patients with LPD, reductions in CSA observed in the right PCUN, right SMG, left IPL, and left LING may be associated with cognitive impairments and hallucinations among non-motor symptoms of PD. Additionally, the SCNs of LPD and RPD patients show significant differences in global topology, but regional node characteristics do not reflect lateralization differences. These findings offer new insights into the mechanisms of symptom lateralization in PD from the perspective of brain regional structure and network topology.

Cortical Thickness Predictors of Performance-Based Functional Task Variability in the Alzheimer Disease Spectrum

PURPOSE

Determine whether regional measures of cortical thickness are associated with functional task performance.

PATIENTS

One hundred six older adults who were classified as either cognitively unimpaired (CU), mild cognitive impairment (MCI), or Alzheimer disease (AD) completed a performance-based functional task.

METHODS

The SD of completion times of 6 consecutive trials within a session of the functional task was used as the primary measure for each participant, reflecting intraindividual variability. Regression tree analysis identified cortical gray matter thickness measures that best predicted intraindividual variability on the functional task.

RESULTS

Cortical thickness measures from temporal, parietal, frontal, and occipital regions best predicted intraindividual variability on the task, which are cortical regions associated with learning, executive function, and visuospatial function. Specifically, the fusiform gyrus was featured prominently in these and prior regression tree results, suggesting its possible involvement in this behavioral task.

CONCLUSION

These analyses suggest a mechanistic focus of variability on this functional task, which could serve as an outcome in clinical trials.

Estimating Multimodal Structural Brain Variability in Schizophrenia Spectrum Disorders: A Worldwide ENIGMA Study

OBJECTIVE

The clinical diversity of schizophrenia is reflected by structural brain variability. It remains unclear how this variability manifests across different gray and white matter features. In this meta- and mega-analysis, the authors investigated how brain heterogeneity in schizophrenia is distributed across multimodal structural indicators.

METHODS

The authors used the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6,037 individuals for a given brain measure. Variability and mean values of cortical thickness, cortical surface area, cortical folding index, subcortical volume, and fractional anisotropy were examined in individuals with schizophrenia and healthy control subjects.

RESULTS

Individuals with schizophrenia showed greater variability in cortical thickness, cortical surface area, subcortical volume, and fractional anisotropy within the frontotemporal and subcortical network. This increased structural variability was mainly associated with psychopathological symptom domains, and the schizophrenia group frequently displayed lower mean values in the respective structural measures. Unexpectedly, folding patterns were more uniform in individuals with schizophrenia, particularly in the right caudal anterior cingulate region. The mean folding values of the right caudal anterior cingulate region did not differ between the schizophrenia and healthy control groups, and folding patterns in this region were not associated with disease-related parameters.

CONCLUSIONS

In patients with schizophrenia, uniform folding patterns in the right caudal anterior cingulate region contrasted with the multimodal variability in the frontotemporal and subcortical network. While variability in the frontotemporal and subcortical network was associated with disease-related diversity, uniform folding may indicate a less flexible interplay between genetic and environmental factors during neurodevelopment.

Alterations in cortical and subcortical neuroanatomy and associations with behavior in females with fragile X syndrome

AIM

To address substantial gaps in the literature on neuroanatomical variations in females with fragile X syndrome (FXS).

METHOD

Surface-based modeling techniques were applied to the magnetic resonance imaging of 45 females with FXS (mean age = 10 years 9 months, range 6 years-16 years 4 months, SD = 2 years 9 months) and 33 age-matched and developmentally matched females without FXS to elucidate differences in cortical gray matter volume, surface area, and thickness. Gray matter volumes in subcortical regions were examined to ascertain differences in subcortical volume.

RESULTS

In females with FXS, cortical volume was greater bilaterally in the occipital pole and smaller in the right postcentral gyrus. Seven regions demonstrated lower surface area in participants with FXS, while cortical thickness was significantly greater over the posterior and medial surfaces in the group with FXS. Subcortical region of interest analyses demonstrated greater volume in the caudate nucleus, globus pallidus, and nucleus accumbens in the group with FXS. Global gray matter volume, pial thickness, and surface area were associated with behavioral outcomes in the group with FXS but not in the comparison group.

INTERPRETATION

Females with FXS demonstrated unique cortical and subcortical gray matter anatomy relative to a matched comparison group. These findings may be relevant to the pathogenesis of the FXS behavioral phenotype and provide insights into behavioral interventions targeted to this population.

Cortical morphometric similarity gradient in schizophrenia and its association with transcriptional profiles and clinical phenotype

BACKGROUND

Recent studies have increasingly utilized gradient metrics to investigate the spatial transitions of brain organization, enabling the conversion of macroscale brain features into low-dimensional manifold representations. However, it remains unclear whether alterations exist in the cortical morphometric similarity (MS) network gradient in patients with schizophrenia (SCZ). This study aims to examine potential differences in the principal MS gradient between individuals with SCZ and healthy controls and to explore how these differences relate to transcriptional profiles and clinical phenomenology.

METHODS

MS network was constructed in this study, and its gradient of the network was computed in 203 patients with SCZ and 201 healthy controls, who shared the same demographics in terms of age and gender. To examine irregularities in the MS network gradient, between-group comparisons were carried out, and partial least squares regression analysis was used to study the relationships between the MS network gradient-based variations in SCZ, and gene expression patterns and clinical phenotype.

RESULTS

In contrast to healthy controls, the principal MS gradient of patients with SCZ was primarily significantly lower in sensorimotor areas, and higher in more areas. In addition, the aberrant gradient pattern was spatially linked with the genes enriched for neurobiologically significant pathways and preferential expression in various brain regions and cortical layers. Furthermore, there were strong positive connections between the principal MS gradient and the symptomatologic score in SCZ.

CONCLUSIONS

These findings showed changes in the principal MS network gradient in SCZ and offered potential molecular explanations for the structural changes underpinning SCZ.

Systematic bias in surface area asymmetry measurements from automatic cortical parcellations

Anatomical asymmetry is a hallmark of the human brain and may reflect hemispheric differences in its functional organization. Widely used software like FreeSurfer can automate neuroanatomical measurements and facilitate studies of hemispheric asymmetry. However, patterns of surface area lateralization measured using FreeSurfer are curiously consistent across diverse samples. Here, we demonstrate systematic biases in these measurements obtained from the default processing pipeline. We compared surface area asymmetry measured from reconstructions of original brains vs. the same scans after flipping their left-right orientation. The default pipeline returned implausible asymmetry patterns between the original and flipped brains: Many structures were always left- or right-lateralized. Notably, these biases occur prominently in key speech and language regions. In contrast, manual labeling and curvature-based parcellations of key structures both yielded the expected reversals of left/right lateralization in flipped brains. We determined that these biases result from discrepancies in how regional labels are defined in the left vs. right hemisphere in the default cortical parcellation atlases. These biases are carried into individual parcellations because the FreeSurfer parcellation algorithm prioritizes vertex correspondence to the template atlas relative to individual neuroanatomical variation. We further demonstrate several straightforward, bias-free approaches to measuring surface area asymmetry, including using symmetric registration templates and parcellation atlases, vertex-wise analyses, and within-subject curvature-based parcellations. These results highlight theoretical concerns about using only the default processing stream to make inferences about population-level brain asymmetry and underscore the need for validating bias-free neuroanatomical measurements, particularly when studying regions where structural lateralization may underlie functional lateralization.

Brain structural magnetic resonance imaging predictors of brief intervention response in individuals with alcohol use disorder

AIMS

Magnetic resonance imaging (MRI) studies have identified brain structural predictors of treatment response in individuals with alcohol use disorder (AUD) but with varying findings and primarily in male veterans. The present study investigated cortical surface area and thickness (CT) as predictors of brief intervention response in community-based adults with AUD.

METHODS

Sixty-five non-treatment-seeking adults with AUD (44.6% male, aged 33.2 ± 1.3 years) underwent an MRI and received a brief intervention comprising personalized feedback and motivational interviewing, with follow-up ~6-8 weeks later to quantify changes in drinks/week (DPW), the primary outcome. Eighteen bilateral a priori regions of interest (ROIs) were used to predict DPW at follow-up, adjusting for baseline drinking. Significant predictors were examined with secondary outcomes, percent drinking and heavy drinking days, and in relation to out-of-scanner measures of impulsivity and comorbidities.

RESULTS

Participants exhibited significant decreases in alcohol consumption in response to the brief intervention. Eight bilateral CT ROIs in the frontal, temporal, and occipital lobes, most notably medial orbitofrontal, middle temporal, and lateral occipital gyri, predicted DPW; however, only three predicted the secondary outcomes. Significant associations were observed between CT in frontal and occipital regions and impulsivity (delay discounting, lack of premeditation), executive functioning, anxiety, and stress.

CONCLUSIONS

Thinner frontal, temporal, and occipital ROIs predicted poorer brief intervention response, with notable overlap with brain regions previously implicated in AUD. Clarifying whether these regions reflect premorbid or acquired differences and, if the latter, the potential for recovery of cortical gray matter following drinking reductions are future priorities.

Dissecting heterogeneity in cortical thickness abnormalities in major depressive disorder: a large-scale ENIGMA MDD normative modelling study

Importance

Major depressive disorder (MDD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology, which may obscure identification of structural brain abnormalities in MDD. To explore this, we used normative modeling to index regional patterns of variability in cortical thickness (CT) across individual patients.

Objective

To use normative modeling in a large dataset from the ENIGMA MDD consortium to obtain individualised CT deviations from the norm (relative to age, sex and site) and examine the relationship between these deviations and clinical characteristics.

Design setting and participants

A normative model adjusting for age, sex and site effects was trained on 35 CT measures from FreeSurfer parcellation of 3,181 healthy controls (HC) from 34 sites (40 scanners). Individualised z-score deviations from this norm for each CT measure were calculated for a test set of 2,119 HC and 3,645 individuals with MDD. For each individual, each CT z-score was classified as being within the normal range (95% of individuals) or within the extreme range (2.5% of individuals with the thinnest or thickest cortices).

Main outcome measures

Z-score deviations of CT measures of MDD individuals as estimated from a normative model based on HC.

Results

Z-score distributions of CT measures were largely overlapping between MDD and HC (minimum 92%, range 92-98%), with overall thinner cortices in MDD. 34.5% of MDD individuals, and 30% of HC individuals, showed an extreme deviation in at least one region, and these deviations were widely distributed across the brain. There was high heterogeneity in the spatial location of CT deviations across individuals with MDD: a maximum of 12% of individuals with MDD showed an extreme deviation in the same location. Extreme negative CT deviations were associated with having an earlier onset of depression and more severe depressive symptoms in the MDD group, and with higher BMI across MDD and HC groups. Extreme positive deviations were associated with being remitted, of not taking antidepressants and less severe symptoms.

Conclusions and relevance

Our study illustrates a large heterogeneity in the spatial location of CT abnormalities across patients with MDD and confirms a substantial overlap of CT measures with HC. We also demonstrate that individualised extreme deviations can identify protective factors and individuals with a more severe clinical picture.

Major depressive disorder on a neuromorphic continuum

The heterogeneity of major depressive disorder (MDD) has hindered clinical translation and neuromarker identification. Biotyping facilitates solving the problems of heterogeneity, by dissecting MDD patients into discrete subgroups. However, interindividual variations suggest that depression may be conceptualized as a "continuum," rather than as a "category." We use a Bayesian model to decompose structural MRI features of MDD patients from a multisite cross-sectional cohort into three latent disease factors (spatial pattern) and continuum factor compositions (individual expression). The disease factors are associated with distinct neurotransmitter receptors/transporters obtained from open PET sources. Increases cortical thickness in sensory and decreases in orbitofrontal cortices (Factor 1) associate with norepinephrine and 5-HT2A density, decreases in the cingulo-opercular network and subcortex (Factor 2) associate with norepinephrine and 5-HTT density, and increases in social and affective brain systems (Factor 3) relate to 5-HTT density. Disease factor patterns can also be used to predict depressive symptom improvement in patients from the longitudinal cohort. Moreover, individual factor expressions in MDD are stable over time in a longitudinal cohort, with differentially expressed disease controls from a transdiagnostic cohort. Collectively, our data-driven disease factors reveal that patients with MDD organize along continuous dimensions that affect distinct sets of regions.

Kawaii-Ness Mediates Between Demographic Variables, Happiness, and Brain Conditions

Background/Objectives: In many societies, especially in highly masculine societies like Japan, being a man, getting older, engaging in knowledge work, and earning a high annual salary are seen as conditions for success. On the other hand, an increasing number of studies have shown that incorporating kawaii-ness into our lives can help maintain and improve happiness and well-being. Methods: Therefore, in this study, we employed a variable expressing the response to kawaii-ness together with four demographic variables (sex, age, income, and knowledge work), happiness, and fractional anisotropy brain healthcare quotient (FA-BHQ) which is derived from magnetic resonance imaging (MRI) images calculations to analyze the relationship between them. Results: The results of a path analysis using data obtained from 182 healthy men and women showed that kawaii-ness mediates the association between demographic variables and happiness, which is in turn associated with FA-BHQ. Furthermore, with the correlation analysis between happiness and individual FA regions, we were able to confirm that FA regions, including the limbic-thalamo-cortical pathway, which is responsible for emotional regulation, are related to happiness. Conclusions: These results indicate the following: Men, older people, people engaged in knowledge work, and people with high annual incomes avoid kawaii-ness; As a result, they are unable to obtain the sense of happiness that they should have; as a result, they are unable to keep their brains healthy, and their brain functions, including emotional regulation, are not functioning properly; This may prevent them from maintaining or improving their performance. This study is the first attempt to clarify the relationship between demographic scales, kawaii-ness, happiness, and brain conditions.

Non-alcoholic fatty liver disease is associated with structural covariance network reconfiguration in cognitively unimpaired adults with type 2 diabetes

Type 2 diabetes (T2D) is often accompanied by non-alcoholic fatty liver disease (NAFLD), both of which are related to brain damage and cognitive impairment. However, cortical structural alteration and its relationship with metabolism and cognition in T2D with NAFLD (T2NAFLD) and without NAFLD (T2noNAFLD) remain unclear. The brain MRI scans, clinical measures and neuropsychological test were evaluated in 50 normal controls (NC), 73 T2noNAFLD, and 58 T2NAFLD. The cortical thickness and graph theory properties of structural covariance network was calculated. Statistical analyses included one-way analysis of covariance with post hoc, partial correlation and mediation analysis. The nonparametric permutation test was performed to evaluate differences in topological properties of structural covariance network. We found T2NAFLD group had worse glucose and lipid profiles, more obesity and more severe insulin resistance, and poorer working memory compared to T2noNAFLD and NC. T2D patients demonstrated increase in cortical thickness compared to NC, but no difference between the two T2D groups. The structural covariance network integration decreased in T2D patients, with T2NAFLD exhibiting more obvious network reconfiguration at node level. Cortical thickness mediated the relationship between post-prandial glucose, waist-hip ratio, and working memory. The findings suggest that cortical thickening may be a compensatory response to reduced network integration, with NAFLD exacerbating regional structural network changes in T2D. This research advances our understanding of how these metabolic comorbidities contribute to cognitive decline, potentially guiding future therapeutic strategies for T2D patients with and without NAFLD.

Brain-Charting Autism and Attention-Deficit/Hyperactivity Disorder Reveals Distinct and Overlapping Neurobiology

BACKGROUND

Autism and attention-deficit/hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology that is still poorly understood. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together and sex differences are often overlooked. Population modeling, often referred to as normative modeling, provides a unified framework for studying age-specific and sex-specific divergences in brain development.

METHODS

Here, we used population modeling and a large, multisite neuroimaging dataset (N = 4255 after quality control) to characterize cortical anatomy associated with autism and ADHD, benchmarked against models of average brain development based on a sample of more than 75,000 individuals. We also examined sex and age differences and relationship with autistic traits and explored the co-occurrence of autism and ADHD.

RESULTS

We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume that was localized to the superior temporal cortex, whereas individuals with ADHD showed more global increases in cortical thickness but lower cortical volume and surface area across much of the cortex. The co-occurring autism+ADHD group showed a unique pattern of widespread increases in cortical thickness and certain decreases in surface area. We also found that sex modulated the neuroanatomy of autism but not ADHD, and there was an age-by-diagnosis interaction for ADHD only.

CONCLUSIONS

These results indicate distinct cortical differences in autism and ADHD that are differentially affected by age and sex as well as potentially unique patterns related to their co-occurrence.

Associations between structural brain changes and blood neurofilament light chain protein in treatment-resistant schizophrenia

OBJECTIVE

Around 30% of people with schizophrenia are refractory to antipsychotic treatment (treatment-resistant schizophrenia). Abnormal structural neuroimaging findings, in particular volume and thickness reductions, are often described in schizophrenia. Novel biomarkers of active brain pathology such as neurofilament light chain protein are now expected to improve current understanding of psychiatric disorders, including schizophrenia. This study explored whether treatment-resistant schizophrenia individuals exhibit different associations between plasma neurofilament light chain protein levels and regional cortical thickness reductions compared with controls.

METHODS

Plasma neurofilament light chain protein levels were measured, and T1-weighted magnetic resonance imaging sequences were obtained and processed via FreeSurfer for each participant. General linear models adjusting for age and body mass index were estimated to determine whether the interaction between diagnostic group and plasma neurofilament light chain protein level predicted lower cortical thickness across frontotemporal structures and the insula.

RESULTS

A total of 79 participants were included: 37 treatment-resistant schizophrenia and 42 healthy controls. Significant (false discovery rate-corrected) cortical thinning of the left (p = 0.005, η2p = 0.100) and right (p = 0.002, η2p = 0.149) insula, and left inferior temporal gyrus (p < 0.001, η2p = 0.143) was associated with higher levels of plasma neurofilament light chain protein in treatment-resistant schizophrenia, but not in healthy controls.

CONCLUSIONS

The association between regional thickness reduction of the bilateral insula and left inferior temporal gyrus with plasma neurofilament light chain protein may reflect a neuroprogressive component to schizophrenia, which is not observed in the normal population.

Atlas of plasma metabolic markers linked to human brain morphology

Background

Metabolic processes form the basis of the development, functioning and maintenance of the brain. Despite accumulating evidence of the vital role of metabolism in brain health, no study to date has comprehensively investigated the link between circulating markers of metabolic activity and in vivo brain morphology in the general population.

Methods

We performed uni- and multivariate regression on metabolomics and MRI data from 24,940 UK Biobank participants, to estimate the individual and combined associations of 249 circulating metabolic markers with 91 measures of global and regional cortical thickness, surface area and subcortical volume. We investigated similarity of the identified spatial patterns with brain maps of neurotransmitters, and used Mendelian randomization to uncover causal relationships between metabolites and the brain.

Results

Intracranial volume and total surface area were highly significantly associated with circulating lipoproteins and glycoprotein acetyls, with correlations up to .15. There were strong regional associations of individual markers with mixed effect directions, with distinct patterns involving frontal and temporal cortical thickness, brainstem and ventricular volume. Mendelian randomization provided evidence of bidirectional causal effects, with the majority of markers affecting frontal and temporal regions.

Discussion

The results indicate strong bidirectional causal relationships between circulating metabolic markers and distinct patterns of global and regional brain morphology. The generated atlas of associations provides a better understanding of the role of metabolic pathways in structural brain development and maintenance, in both health and disease.

Cortical lesions impact cognitive decline in multiple sclerosis via volume loss of nonlesional cortex

OBJECTIVE

To assess the interrelationship between cortical lesions and cortical thinning and volume loss in people with multiple sclerosis within cortical networks, and how this relates to future cognition.

METHODS

In this longitudinal study, 230 people with multiple sclerosis and 60 healthy controls underwent 3 Tesla MRI at baseline and neuropsychological assessment at baseline and 5-year follow-up. Cortical regions (N = 212) were divided into seven functional networks. Regions were defined as either lesional or normal-appearing cortex based on presence of a cortical lesion on artificial intelligence-generated double inversion-recovery scans. Cortical volume and thickness were determined within lesional or normal-appearing cortex.

RESULTS

Prevalence of at least one cortical lesion was highest in the limbic (73%) followed by the default mode network (70.9%). Multiple sclerosis-related cortical thinning was more pronounced in lesional (mean Z-score = 0.70 ± 0.84) compared to normal-appearing cortex (-0.45 ± 0.60; P < 0.001) in all, except sensorimotor, networks. Cognitive dysfunction, particularly of verbal memory, visuospatial memory, and inhibition, at follow-up was best predicted by baseline network volume of normal-appearing cortex of the default mode network [B (95% CI) = 0.31 (0.18; 0.43), P < 0.001]. Mediation analysis showed that the effect of cortical lesions on future cognition was mediated by volume loss of the normal-appearing instead of lesional cortex, independent of white matter lesion volume.

INTERPRETATION

Multiple sclerosis-related cortical thinning was worse in lesional compared to normal-appearing cortex, while volume loss of normal-appearing cortex was most predictive of subsequent cognitive decline, particularly in the default mode network. Mediation analyses indicate that cortical lesions impact cognitive decline plausibly by inducing atrophy, rather than through a direct effect.

Structural and Molecular Imaging of Aging Brain: A Focus on MR Imaging and PET Modalities

The process of aging in the brain is reflective of various factors including the environment, lifestyle, genetics, and management of concurrent chronic conditions. Aging in the brain leads to observable structural changes on neuroimaging, such as brain volume reduction, neuronal atrophy, and synaptic loss, which affect higher cognitive functions. Positron emission tomography imaging can help visualize these changes earlier before structural changes even take place and the associated decline in brain function, revealing important insights into how the brain ages and the impact on neural connectivity and cognitive abilities.

An examination of cortical thickness relationships within the reading network of adults

Much brain imaging work has underscored the functional connections among the inferior frontal gyrus (IFG; articulation), supramarginal gyrus (SMG; letter-sound correspondence), superior temporal gyrus (STG; sound) and fusiform gyrus (FFG; print) during basic reading processes. This reading network supports and coordinates the complex processes that contribute to successful reading. In line with the Hebbian notion that 'neurons that fire together, wire together' we examined cortical thickness among these regions and the extent to which these regions showed structural relationships in average and impaired readers. Structural high resolution brain scans from 87 adult participants including average (N = 56; 51 right-handed; females = 29; mean age = 20.5; SD = 2.14) and impaired (N = 31; 27 right-handed; females = 24; mean age = 23.1; SD = 4.23) readers were collated. Cortical thickness measurements of the left and right IFG, SMG, STG, and FFG were extracted. Average readers had significantly greater cortical thickness in the right IFG and right SMG compared to impaired readers. Within each group, similarly strong relationships between the left and right structures were observed. Average readers had a significantly stronger connection between the left IFG-FFG compared to impaired readers (p = 0.012). In contrast, the impaired readers had a significantly stronger connection between the left STG-FFG compared to average readers (p = 0.027). In conclusion, the findings suggest that structural relationships within the reading network may contribute to variations in reading proficiency, with average readers exhibiting distinct patterns of cortical thickness and relationships compared to impaired readers. Further exploration of these structural differences could offer valuable insights into the neural mechanisms underlying reading abilities and disabilities.

Disentangling the unique contributions of age, pubertal stage, and pubertal hormones to brain structure in childhood and adolescence

Puberty and associated changes in pubertal hormones influence structural brain development. Hormones such as dehydroepiandrosterone (DHEA) and progesterone remain understudied, and it remains unclear how these aspects of puberty contribute uniquely to structural brain development. We used the Human Connectome Project in Development cross-sectional sample of 1304 youth (aged 5-21 years) to investigate unique contributions of sex, age, pubertal stage, DHEA, testosterone, estradiol, and progesterone to cortical thickness, surface area, and subcortical volume development within functionally-relevant networks. Sex and age explain the most unique variance in all three aspects of structural development. Pubertal stage and pubertal hormones uniquely contribute more to cortical surface area, compared to thickness. Among the pubertal hormones, progesterone contributed unique variance to surface area in the default mode network, as well as to thickness in the orbito-affective network. Pubertal mechanisms also contributed unique variance to subcortical volumes. This demonstrates unique relations of understudied pubertal hormones to brain structure development and may help understand risk for psychopathology.

Neurostructural features predict binge drinking in emerging adulthood: Evidence from a 5-year follow-up study

BACKGROUND

Binge drinking (BD) involves consuming large amounts of alcohol within a short timeframe, leading to a blood alcohol concentration of 0.08g/dL or above. This pattern of alcohol consumption is prevalent among young adults and has significant implications for brain structure and subsequent drinking behaviors.

METHODS

In this prospective longitudinal study, we employed zero-inflated negative binomial regression models to examine whether various neurostructural features (i.e., volume, surface area, cortical thickness) of brain regions involved in executive and emotional/motivational processes at the age of 18-19 could predict number of BD episodes five years later, at ages 23-24, once participants were expected to complete their university degree. Specifically, we recorded magnetic resonance imaging (MRI) data from 68 students who completed both the baseline MRI and follow-up alcohol use assessment, with the aim of analyzing the predictive value of these neurostructural characteristics five years later.

RESULTS

The analysis revealed that a larger surface area in the caudal division of the right middle frontal gyrus was significantly associated with a higher incidence rate of BD episodes (IRR = 2.24, 95 % CI = 1.28-3.91, p = 0.005). Conversely, a smaller surface area in the right caudal anterior cingulate cortex was associated with a higher incidence rate of BD episodes (IRR = 0.61, 95 % CI = 0.44-0.85, p = 0.004).

CONCLUSIONS

These findings suggest that specific neurostructural characteristics during adolescence can predict BD behaviors in young adulthood. This highlights the potential of neuroimaging to identify individuals at risk for developing problematic alcohol use.

Concurrent and longitudinal neurostructural correlates of irritability in children

Irritability, or an increased proneness to frustration and anger, is common in youth; however, few studies have examined neurostructural correlates of irritability in children. The purpose of the current study was to examine concurrent and longitudinal associations between brain structure and irritability in a large sample of 9-10-year-old children. Participants included 10,647 children from the Adolescent Brain Cognitive Developmentsm Study (ABCD Study®). We related a latent irritability factor to gray matter volume, cortical thickness, and surface area in 68 cortical regions and to gray matter volume in 19 subcortical regions using structural equation modeling. Multiple comparisons were adjusted for using the false discovery rate (FDR). After controlling for age, sex, race/ethnicity, scanner model, parent's highest level of education, medication use, and total intracranial volume, irritability was associated with smaller volumes in primarily temporal and parietal regions at baseline. Longitudinal analyses showed that baseline gray matter volume did not predict irritability symptoms at the 3rd-year follow-up. No significant associations were found for cortical thickness or surface area. The current study demonstrates inverse associations between irritability and volume in regions implicated in emotional processing/social cognition, attention allocation, and movement/perception. We advance prior research by demonstrating that neurostructural differences associated with irritability are already apparent by age 9-10 years, extending this work to children and supporting theories positing socioemotional deficits as a key feature of irritability.

Shared and distinct alterations in brain morphology in children with ADHD and obesity: Reduced cortical surface area in ADHD and thickness in overweight/obesity

OBJECTIVE

To investigate shared versus distinct differences in brain structure among children with ADHD and obesity, we examined the morphology of regions implicated in cognitive control and reward function in a single cross-sectional cohort of children with and without ADHD and overweight/obesity (OV/OB).

METHOD

Participants included 471 children ages 8-12 years with ADHD (n = 244; 58 OV/OB) and neurotypical (NT) controls (n = 227; 81 OV/OB) classified as healthy-weight (HW; BMI %ile 5th to <85th) vs. having OV/OB (BMI %ile≥85th). Structural MRI was performed to obtain measures of cortical and subcortical morphology and compared across ADHD × BMI groups.

RESULTS

Surface area was generally lower in ADHD vs. NT including in anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (dlPFC), medial (m)PFC, and primary motor (M1) cortex. In contrast, cortical thickness was generally lower in OV/OB vs. HW for ACC, dlPFC, orbitofrontal cortex (OFC), mPFC, and supplementary motor cortex (SMC). Furthermore, ADHD × OV/OB interactions were observed for the ACC and OFC, with the lowest ACC volume in the ADHD + OV/OB group and the highest OFC surface area in the NT + OV/OB group. Subcortical volumes did not differ between groups.

CONCLUSIONS

Our findings reveal distinct alterations in cortical morphology in association with ADHD and overweight, with cortical surface area reduced in ADHD vs. thickness reduced in OV/OB. Additionally, the findings provide evidence of combined effects of ADHD × OV/OB in brain regions integral to cognition and motivation. Our results support further investigation of causes and correlates of shared and distinct ADHD- and OV/OB-associated differences in developing frontocingulate morphology.

APOE4 and Chronic Health Risk Factors are Associated with Sex-Specific Preclinical Alzheimer's Disease Neuroimaging Biomarkers

Introduction

Two thirds of Alzheimer's disease (AD) patients are female. Genetic and chronic health risk factors for AD affect females more negatively compared to males.

Objective

This exploratory multimodal neuroimaging study aimed to examine sex differences in cognitively unimpaired older adults on: (1) amyloid-β via 18F-AV-45 Florbetapir PET imaging, (2) neurodegeneration via T1 weighted MRI volumetrics, (3) cerebral blood flow via ASL-MRI. We identified AD risk factors including genetic (APOE genotype status) and health markers (fasting glucose, mean arterial pressure, waist-to-hip ratio, and android and gynoid body fat) associated with neuroimaging outcomes for which we observed sex differences.

Methods

Participants were sedentary, amyloid-β positive older adults (N = 112, ages 65-87 years) without evidence of cognitive impairment (CDR = 0).

Results

Multivariate analysis of covariance models adjusted for intracranial volume, age, and years of education demonstrated lower volume (F (7, 102) = 2.67, p = 0.014) and higher blood flow F (6, 102) = 4.25, p =<0.001) among females compared to males in regions of interest connected to AD pathology and the estrogen receptor network. We did not observe sex differences in amyloid-β levels. Higher than optimal waist to hip ratio was most strongly associated with lower volume, while higher android fat percentage and APOE ε4 carrier status were most strongly associated with higher blood flow among female participants.

Discussion

Findings suggest genetic and chronic health risk factors are associated with sex-specific AD neuroimaging biomarkers. Underlying sex-specific biological pathways may explain these findings. Our results highlight the importance of considering sex differences in neuroimaging studies and when developing effective interventions for AD prevention and risk reduction.

Structural Brain Correlates of Anxiety During Development

Anxiety and related disorders are prevalent across the lifespan, often have their onset during youth, and are associated with notable levels of impairment and burden across multiple domains. Elucidating the associations between differential patterns of neurodevelopment and anxiety in youth is a promising approach for developing deeper insights regarding the neurobiological etiologies and maintenance factors associated with anxiety and related disorders. A growing body of literature has yielded evidence of associations between patterns of brain structure (i.e., volume, cortical thickness, and cortical surface area) and anxiety. Here, we present a review and synthesis of the existing body of literature surrounding neurostructural correlates of anxiety in youth spanning multiple anxiety presentations and three neurostructural modalities. We reveal substantially more research focusing on brain volume than cortical thickness or surface area and a greater number of studies examining anxiety broadly defined, obsessive-compulsive disorder, or posttraumatic stress disorder. There is also evidence of considerable variability in the brain regions implicated and the direction of associations across studies. Finally, we discuss the gaps and limitations in this body of work, which suggest avenues for future directions.

Mapping grey matter and cortical thickness alterations associated with subjective cognitive decline and mild cognitive impairment among rural-dwelling older adults in China: A population-based study

BACKGROUND

The structural brain alterations for subjective cognitive decline (SCD) and mild cognitive impairment (MCI) are poorly defined. We sought to characterize grey matter volume (GMV) and cortical thickness associated with SCD and MCI among rural-dwelling older adults in China.

METHODS

This population-based cross-sectional study included 1072 dementia-free participants from the brain MRI sub-study of MIND-China (2018-2020). We defined MCI following the Petersen's criteria, and SCD as the self-rated Ascertain Dementia 8-item Questionnaire score ≥ 2. Data were analyzed using voxel-based morphometry (VBM), surface-based morphometry analysis (SBM), and logistic regression models.

RESULTS

SCD was defined in 243 persons and MCI in 246 individuals. The VBM analysis showed that MCI (vs. normal cognition) was significantly associated with reduced GMV in brain regions such as the bilateral parahippocampus, bilateral hippocampus, and bilateral fusiform (P < 0.05), but SCD exhibited no significant differences with normal cognition in GMV (P > 0.05). The ROI-wise SBM analysis revealed that SCD was significantly associated with cortical thinning in the right paracentral sulcus, left caudal middle frontal gyrus, and left entorhinal cortex (P < 0.05) and that MCI was significantly associated with cortical thinning in the left temporal lobe, left frontal lobe, bilateral parietal lobe and bilateral fusiform (P < 0.05).

CONCLUSIONS

The brain regions with reduced GMV or cortical thickness in older adults gradually expand from normal cognition through SCD to MCI, suggesting that characterizing structural brain alterations may help define the cognitive spectrum at the pre-dementia phase. These findings have potential implications for understanding the neuropathological process of cognitive deterioration in aging.

Quantitative MRI Measures and Cognitive Function in People With Drug-Resistant Juvenile Myoclonic Epilepsy

BACKGROUND AND OBJECTIVES

Neuroimaging studies have so far identified structural changes in individuals with juvenile myoclonic epilepsy (JME) when compared with controls. However, the underlying mechanisms of drug-resistant JME remain unknown. In this study, we aimed at characterizing the structural underpinnings of drug-resistant JME using MRI-derived cortical morphologic markers.

METHODS

In this prospective cross-sectional 2-center study, T1-weighted MRI and neuropsychological measures of verbal memory and executive function were obtained in individuals with drug-resistant and drug-responsive JME recruited from epilepsy outpatient clinics and healthy controls. We performed vertexwise measurements of cortical thickness, surface area, and local gyrification index (LGI). Vertexwise group comparisons were corrected for multiple comparisons at a familywise error (FWE) of 0.05. The neuropsychological profile of disease subgroups was analyzed through principal component analysis.

RESULTS

We studied 42 individuals with drug-resistant JME (mean age 29 ± 11 years, 50% female), 37 with drug-responsive JME (mean age 34 ± 10, years, 59% female), and 71 healthy controls (mean age 21 ± 9 years, 61% female). Surface area was increased in participants with drug-resistant JME in the left temporal lobe (Cohen d = 0.82 [-0.52 to -1.12], pFWE < 0.05) when compared with the drug-responsive group. Although no cortical thickness changes were observed between disease subgroups, drug-resistant and drug-sensitive participants showed discrete cortical thinning against controls (Cohen d = -0.42 [-0.83 to -0.01], pFWE < 0.05; Cohen d = -0.57 [-1.03 to -0.11], pFWE < 0.05, respectively). LGI was increased in the left temporal and occipital lobes in drug-resistant participants (Cohen d = 0.60 [0.34-0.86], pFWE < 0.05) when contrasting against drug-sensitive participants, but not controls. The composite executive function score was reduced in drug-resistant individuals compared with controls and drug-sensitive individuals (-1.74 [-2.58 to -0.90], p < 0.001 and -1.29 [-2.25 to -0.33], p < 0.01, respectively). Significant correlations were observed between executive function impairment and increased surface area in the precuneus and medial prefrontal regions (r = -0.79, pFWE < 0.05) in participants with drug-resistant JME.

DISCUSSION

We identified a developmental phenotype in individuals with drug-resistant JME characterized by changes in cortical surface area and folding complexity, the extent of which correlates with executive dysfunction. No association was observed between cortical thickness and disease severity. Our findings support a neurodevelopmental basis for drug resistance and cognitive impairment in JME.

Genetic and vascular risk factors for ischemic stroke and cortical morphometry in individuals without a history of stroke: A UK Biobank observational cohort study

BACKGROUND

Stroke risk factors may contribute to cognitive decline and dementia by altering brain tissue integrity. If their effects on brain are nonnegligible, the target regions for stroke rehabilitation with brain stimulation identified by cross-sectional case-control studies may be biased due to the pre-existing brain differences caused by these risk factors. Here, we investigated the effects of stroke risk factors on cortical thickness (CT) and surface area (SA) in individuals without a history of stroke.

METHODS

In this observational study, we used data from the UK Biobank cohort to explore the effects of polygenic risk score for ischemic stroke (PRSIS), systolic blood pressure (SBP), diastolic blood pressure (DBP), glycated hemoglobin (HbA1c), triglycerides (TG), and low-density lipoprotein (LDL) on CT and SA of 62 cerebral regions. We excluded non-Caucasian participants and participants with missing data, unqualified brain images, or a history of stroke or any other brain diseases. We constructed a multivariate linear regression model for each phenotype to simultaneously test the effect of each factor and interaction between factors. The results were verified by sensitivity analyses of SDP or DBP input and adjusting for body-mass index, high-density lipoprotein cholesterol, or smoking and alcohol intake. By excluding participants with abnormal blood pressure, glucose, or lipid, we tested whether vascular risk factor within normal range also affected cortical phenotypes. To determine clinical relevance of our findings, we also investigated the effects of stroke risk factors and cortical phenotypes on cognitive decline assessed by fluid intelligence score (FIQ) and the mediation of cortical phenotype for the association between stroke risk factor and FIQ.

RESULTS

The study consisted of 27 120 eligible participants. Stroke risk factors were associated with 16 CT and two SA phenotypes in both main and sensitivity analyses (all p < 0.0004, Bonferroni corrected), which could explain portions of variances (partial R2, median 0.62 % [IQR 0.44-0.75 %] in main analyses) in these phenotypes. Among the 18 cortical phenotypes associated with stroke risk factors, we identified 26 specific predictor-phenotype associations (all p < 0.0026), including the positive associations between PRSIS and SA and between HbA1c and CT, negative associations of SBP and TG with CT, and mixed associations of PRSIS and DBP with CT. Neither LDL nor interactions between risk factors affected cortical phenotypes. Of the 16 associations between vascular risk factors and cortical phenotypes, ten were still significant after excluding participants with abnormal vascular risk assessments and diagnoses. Stroke risk factors were associated with FIQ in all analyses (p < 0.0004; partial R2, range 0.22-0.3 %), of which the associations of PRSIS and SBP with cognitive decline were mediated by CT phenotypes.

CONCLUSIONS

Stroke risk factors have substantial effects on cortical morphometry and cognitive decline in middle-aged and older people, which should be considered in the prevention of dementia and in the identification of target regions for stroke rehabilitation with brain stimulation.

Influence of intergenerational social mobility on brain structure and global cognition: findings from the Whitehall II study across 20 years

BACKGROUND

Whether changes in socioeconomic position (SEP) across generations, i.e. intergenerational social mobility, influence brain degeneration and cognition in later life is unclear.

OBJECTIVE

To examine the association of social mobility, brain grey matter structure and global cognition.

METHODS

We analysed T1 brain MRI data of 771 old adults (69.8 ± 5.2 years) from the Whitehall II MRI substudy, with MRI data collected between 2012 and 2016. Social mobility was defined by SEP changes from their fathers' generation to mid-life status. Brain structural outcomes include grey matter (GM) volume and cortical thickness (CT) covering whole brain. Global cognition was measured by the Mini Mental State Examination. We firstly conducted analysis of covariance to identify regional difference of GM volume and cortical thickness across stable high/low and upward/downward mobility groups, followed with diagonal reference models studying the relationship between mobility and brain cognitive outcomes, apart from SEP origin and destination. We additionally conducted linear mixed models to check mobility interaction over time, where global cognition was derived from three phases across 2002 to 2017.

RESULTS

Social mobility related to 48 out of the 136 GM volume regions and 4 out of the 68 CT regions. Declined volume was particularly seen in response to downward mobility, whereas no independent association of mobility with global cognition was observed.

CONCLUSION

Despite no strong evidence supporting direct influence of mobility on global cognition in later life, imaging findings warranted a severe level of neurodegeneration due to downward mobility from their father's generation.

Longitudinal neuroanatomical increases from early to one-year postpartum

Preclinical studies have provided causal evidence that the postpartum period involves regional neuroanatomical changes in 'maternal' brain regions to support the transition to offspring caregiving. Few studies, in humans, have examined neuroanatomical changes from early to one-year postpartum with longitudinal neuroimaging data and their association with postpartum mood changes. In the present study, we examined longitudinal changes in surface morphometry (cortical thickness and surface area) in regions previously implicated in the transition to parenthood. We also examined longitudinal volumetric neuroanatomical changes in three subcortical regions of the maternal brain: the hippocampus, amygdala, and ventral diencephalon. Twenty-four participants underwent longitudinal structural magnetic resonance imaging at 1-4 weeks and 1 year postpartum. Cortical thickness increased from early to one-year postpartum in the left (p = .003, Bonferroni corrected) and right (p = .02, Bonferroni corrected) superior frontal gyrus. No significant increases (or decreases) were observed in these regions for surface area. Volumetric increases, across the postpartum period, were found in the left amygdala (p = .001, Bonferroni corrected) and right ventral diencephalon (p = .01, Bonferroni corrected). An exploratory analysis of depressive symptoms found reductions in depressive symptoms from early postpartum to one-year postpartum were associated with greater cortical thickness in the superior frontal gyrus for both the left (p = .02) and right (p = .02) hemispheres. The findings expand our evidence of the neuroanatomical changes that occur across the postpartum period in humans and motivate future studies to examine how mood changes across this period are associated with cortical thickness of the superior frontal gyrus.

Medial prefrontal neuroplasticity during extended-release naltrexone treatment of opioid use disorder - a longitudinal structural magnetic resonance imaging study

Opioid use disorder (OUD) has been linked to macroscopic structural alterations in the brain. The monthly injectable, extended-release formulation of μ-opioid antagonist naltrexone (XR-NTX) is highly effective in reducing opioid craving and preventing opioid relapse. Here, we investigated the neuroanatomical effects of XR-NTX by examining changes in cortical thickness during treatment for OUD. Forty-seven OUD patients underwent structural magnetic resonance imaging and subjectively rated their opioid craving ≤1 day before (pre-treatment) and 11 ± 3 days after (on-treatment) the first XR-NTX injection. A sample of fifty-six non-OUD individuals completed a single imaging session and served as the comparison group. A publicly available [¹¹C]carfentanil positron emission tomography dataset was used to assess the relationship between changes in cortical thickness and μ-opioid receptor (MOR) binding potential across brain regions. We found that the thickness of the medial prefrontal and anterior cingulate cortices (mPFC/aCC; regions with high MOR binding potential) was comparable between the non-OUD individuals and the OUD patients at pre-treatment. However, among the OUD patients, mPFC/aCC thickness significantly decreased from pre-treatment to on-treatment. A greater reduction in mPFC/aCC thickness was associated with a greater reduction in opioid craving. Taken together, our study suggests XR-NTX-induced cortical thickness reduction in the mPFC/aCC regions in OUD patients. The reduction in thickness does not appear to indicate a restoration to the non-OUD level but rather reflects XR-NTX's distinct therapeutic impact on an MOR-rich brain structure. Our findings highlight the neuroplastic effects of XR-NTX that may inform the development of novel OUD interventions.

Face-brain correlates as potential sex-specific biomarkers for schizophrenia and bipolar disorder

Given the shared ectodermal origin and integrated development of the face and the brain, facial biomarkers emerge as potential candidates to assess vulnerability for disorders in which neurodevelopment is compromised, such as schizophrenia (SZ) and bipolar disorder (BD). The sample comprised 188 individuals (67 SZ patients, 46 BD patients and 75 healthy controls (HC)). Using a landmark-based approach on 3D facial reconstructions, we quantified global and local facial shape differences between SZ/BD patients and HC using geometric morphometrics. We also assessed correlations between facial and brain cortical measures. All analyses were performed separately by sex. Diagnosis explained 4.1 % - 5.9 % of global facial shape variance in males and females with SZ, and 4.5 % - 4.1 % in BD. Regarding local facial shape, we detected 43.2 % of significantly different distances in males and 47.4 % in females with SZ as compared to HC, whereas in BD the percentages decreased to 35.8 % and 26.8 %, respectively. We detected that brain area and volume significantly explained 2.2 % and 2 % of facial shape variance in the male SZ - HC sample. Our results support facial shape as a neurodevelopmental marker for SZ and BD and reveal sex-specific pathophysiological mechanisms modulating the interplay between the brain and the face.

Convergent Neuroimaging and Molecular Signatures in Mild Cognitive Impairment and Alzheimer's Disease: A Data-Driven Meta-Analysis with N = 3,118

The current study aimed to evaluate the susceptibility to regional brain atrophy and its biological mechanism in Alzheimer's disease (AD). We conducted data-driven meta-analyses to combine 3,118 structural magnetic resonance images from three datasets to obtain robust atrophy patterns. Then we introduced a set of radiogenomic analyses to investigate the biological basis of the atrophy patterns in AD. Our results showed that the hippocampus and amygdala exhibit the most severe atrophy, followed by the temporal, frontal, and occipital lobes in mild cognitive impairment (MCI) and AD. The extent of atrophy in MCI was less severe than that in AD. A series of biological processes related to the glutamate signaling pathway, cellular stress response, and synapse structure and function were investigated through gene set enrichment analysis. Our study contributes to understanding the manifestations of atrophy and a deeper understanding of the pathophysiological processes that contribute to atrophy, providing new insight for further clinical research on AD.

Accuracy and efficiency of finite element head models: The role of finite element formulation and material laws

Traumatic brain injury is a significant problem worldwide. In the United States of America, around 1.7 million cases are documented annually, displaying the need for a deeper understanding of the effects on the human brain. The tests required for this assessment are very complex. Tests on cadavers may raise serious ethical questions, and in vivo crash tests are not viable. In this context, there is a great need to developing finite element head models (FEHM) to study the biomechanics of the tissues when submitted to a certain impact or acceleration/deceleration scenario. An excellent compromise between accuracy and CPU efficiency is always desirable for a FEHM, For this reason, this work focuses on the improvement of an existing head model, including the study of the behavior of the brain using distinct finite element types. The finite element type and formulation is of utmost importance for the general accuracy and efficiency of the models. Several validations were performed, comparing the simulation results against experimental data. The simulations with hexahedral elements, under specific conditions, obtained more accurate results with a lower computational cost. Using hexahedrals, a comparison was also performed using two material characterizations with more than 10 years apart, using the latest finite element head model validation experiment. Overall, the newer material model displays a less stiff response, although its implementation must always depend on the overall purpose of the model it is being applied to.

Joint modeling of human cortical structure: Genetic correlation network and composite-trait genetic correlation

Heritability and genetic covariance/correlation quantify the marginal and shared genetic effects across traits. They offer insights on the genetic architecture of complex traits and diseases. To explore how genetic variations contribute to brain function variations, we estimated heritability and genetic correlation across cortical thickness, surface area, and volume of 33 anatomically predefined regions in left and right hemispheres, using summary statistics of genome-wide association analyses of 31,968 participants in the UK Biobank. To characterize the relationships between these regions of interest, we constructed a genetic network for these regions using recursive two-way cut-offs in similarity matrices defined by genetic correlations. The inferred genetic network matches the brain lobe mapping more closely than the network inferred from phenotypic similarities. We further studied the associations between the genetic network for brain regions and 30 complex traits through a novel composite-linkage disequilibrium score regression method. We identified seven significant pairs, which offer insights on the genetic basis for regions of interest mediated by cortical measures.

Identifying novel data-driven subgroups in congenital heart disease using multi-modal measures of brain structure

Individuals with congenital heart disease (CHD) have an increased risk of neurodevelopmental impairments. Given the hypothesized complexity linking genomics, atypical brain structure, cardiac diagnoses and their management, and neurodevelopmental outcomes, unsupervised methods may provide unique insight into neurodevelopmental variability in CHD. Using data from the Pediatric Cardiac Genomics Consortium Brain and Genes study, we identified data-driven subgroups of individuals with CHD from measures of brain structure. Using structural magnetic resonance imaging (MRI; N = 93; cortical thickness, cortical volume, and subcortical volume), we identified subgroups that differed primarily on cardiac anatomic lesion and language ability. In contrast, using diffusion MRI (N = 88; white matter connectivity strength), we identified subgroups that were characterized by differences in associations with rare genetic variants and visual-motor function. This work provides insight into the differential impacts of cardiac lesions and genomic variation on brain growth and architecture in patients with CHD, with potentially distinct effects on neurodevelopmental outcomes.

Transcriptomic decoding of regional cortical vulnerability to major depressive disorder

Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls. Combined with the Allen Human Brain Atlas, we then adopted transcription-neuroimaging spatial correlation and the newly developed ensemble-based gene category enrichment analysis to identify gene categories with expression related to cortical changes in MDD. Results showed that patients had relatively circumscribed impairments in local functional properties and broadly distributed disruptions in global functional connectivity, consistently characterized by hyper-function in associative areas and hypo-function in primary regions. Moreover, the local functional alterations were correlated with genes enriched for biological functions related to MDD in general (e.g., endoplasmic reticulum stress, mitogen-activated protein kinase, histone acetylation, and DNA methylation); and the global functional connectivity changes were associated with not only MDD-general, but also brain-relevant genes (e.g., neuron, synapse, axon, glial cell, and neurotransmitters). Our findings may provide important insights into the transcriptomic signatures of regional cortical vulnerability to MDD.

Genetic and environmental influences on structural brain development from childhood to adolescence: A longitudinal twin study on cortical thickness, surface area, and subcortical volume

The human brain undergoes structural development from childhood to adolescence, with specific regions in the sensorimotor, social, and affective networks continuing to grow into adulthood. While genetic and environmental factors contribute to individual differences in these brain trajectories, the extent remains understudied. Our longitudinal study, utilizing up to three biennial MRI scans (n=485), aimed to assess the genetic and environmental effects on brain structure (age 7) and development (ages 7-14) in these regions. Heritability estimates varied across brain regions, with all regions showing genetic influence (ranging from 18 % to 59 %) with additional shared environmental factors affecting the primary motor cortex (30 %), somatosensory cortex (35 %), DLPFC (5 %), TPJ (17 %), STS (17 %), precuneus (10 %), hippocampus (22 %), amygdala (5 %), and nucleus accumbens (10 %). Surface area was more genetically driven (38 %) than cortical thickness (14 %). Longitudinal brain changes were primarily driven by genetics (ranging from 1 % to 29 %), though shared environment factors (additionally) influenced the somatosensory cortex (11 %), DLPFC (7 %), cerebellum (28 %), TPJ (16 %), STS (20 %), and hippocampus (17 %). These findings highlight the importance of further investigating brain-behavior associations and the influence of enriched and deprived environments from childhood to adolescence. Ultimately, our study can provide insights for interventions aimed at supporting children's development.

Exploring Neuroimaging Association Scores in adulthood ADHD and middle-age trajectories

Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder associated with brain differences in children, but not in adults. A combined evaluation of the regional brain differences could improve statistical power and, consequently, allow the detection of possible effects in adults. Thus, our aim is to verify whether Neuroimaging Association Scores (NAS) are associated with adulthood ADHD and clinical trajectories of the disorder in midlife. Clinical and neuroimaging data were collected for 121 subjects with ADHD (mean age: 47.1 ± 10.5; 43% male) and 82 controls (mean age: 38.2 ± 9.0; 54.9% male). Cases were assessed seven and thirteen years after baseline diagnosis, and their clinical trajectories were classified as stable if they fulfilled ADHD diagnosis in all assessments or unstable if they presented remission and recurrence of symptoms. Neuroimaging data were acquired in the last clinical assessment (thirteen years after baseline) and NAS were calculated as a weighted sum of the associations previously reported by meta-analyses for three types of structural brain modalities: cortical thickness, cortical surface area, and subcortical volume. The NAS for cortical surface area was higher in cases compared to controls. No association was found for NAS and number of symptoms of ADHD or clinical trajectories. The fact that differences were restricted to ADHD diagnostic status suggests a susceptibility effect that is not extended to subtle aspects of the disorder. Our results also suggest that evaluating overall effects may have advantages especially when applied to adult ADHD samples.

The Genetic Architecture of the Human Corpus Callosum and its Subregions

The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses, performing associative/executive functions, and representing information in multiple dimensions. Understanding which genetic variants underpin corpus callosum morphometry, and their shared influence on cortical structure and susceptibility to neuropsychiatric disorders, can provide molecular insights into the CC's role in mediating cortical development and its contribution to neuropsychiatric disease. To characterize the morphometry of the midsagittal corpus callosum, we developed a publicly available artificial intelligence based tool to extract, parcellate, and calculate its total and regional area and thickness. Using the UK Biobank (UKB) and the Adolescent Brain Cognitive Development study (ABCD), we extracted measures of midsagittal corpus callosum morphometry and performed a genome-wide association study (GWAS) meta-analysis of European participants (combined N = 46,685). We then examined evidence for generalization to the non-European participants of the UKB and ABCD cohorts (combined N = 7,040). Post-GWAS analyses implicate prenatal intracellular organization and cell growth patterns, and high heritability in regions of open chromatin, suggesting transcriptional activity regulation in early development. Results suggest programmed cell death mediated by the immune system drives the thinning of the posterior body and isthmus. Global and local genetic overlap, along with causal genetic liability, between the corpus callosum, cerebral cortex, and neuropsychiatric disorders such as attention-deficit/hyperactivity and bipolar disorders were identified. These results provide insight into variability of corpus callosum development, its genetic influence on the cerebral cortex, and biological mechanisms related to neuropsychiatric dysfunction.

Profiling cortical morphometric similarity in perinatal brains: Insights from development, sex difference, and inter-individual variation

The topological organization of the macroscopic cortical networks important for the development of complex brain functions. However, how the cortical morphometric organization develops during the third trimester and whether it demonstrates sexual and individual differences at this particular stage remain unclear. Here, we constructed the morphometric similarity network (MSN) based on morphological and microstructural features derived from multimodal MRI of two independent cohorts (cross-sectional and longitudinal) scanned at 30-44 postmenstrual weeks (PMW). Sex difference and inter-individual variations of the MSN were also examined on these cohorts. The cross-sectional analysis revealed that both network integration and segregation changed in a nonlinear biphasic trajectory, which was supported by the results obtained from longitudinal analysis. The community structure showed remarkable consistency between bilateral hemispheres and maintained stability across PMWs. Connectivity within the primary cortex strengthened faster than that within high-order communities. Compared to females, male neonates showed a significant reduction in the participation coefficient within prefrontal and parietal cortices, while their overall network organization and community architecture remained comparable. Furthermore, by using the morphometric similarity as features, we achieved over 65 % accuracy in identifying an individual at term-equivalent age from images acquired after birth, and vice versa. These findings provide comprehensive insights into the development of morphometric similarity throughout the perinatal cortex, enhancing our understanding of the establishment of neuroanatomical organization during early life.

Heritability of functional gradients in the human subcortico-cortical connectivity

The human subcortex plays a pivotal role in cognition and is widely implicated in the pathophysiology of many psychiatric disorders. However, the heritability of functional gradients based on subcortico-cortical functional connectivity remains elusive. Here, leveraging twin functional MRI (fMRI) data from both the Human Connectome Project (n = 1023) and the Adolescent Brain Cognitive Development study (n = 936) datasets, we construct large-scale subcortical functional gradients and delineate an increased principal functional gradient pattern from unimodal sensory/motor networks to transmodal association networks. We observed that this principal functional gradient is heritable, and the strength of heritability exhibits a heterogeneous pattern along a hierarchical unimodal-transmodal axis in subcortex for both young adults and children. Furthermore, employing a machine learning framework, we show that this heterogeneous pattern of the principal functional gradient in subcortex can accurately discern the relationship between monozygotic twin pairs and dizygotic twin pairs with an accuracy of 76.2% (P < 0.001). The heritability of functional gradients is associated with the anatomical myelin proxied by MRI-derived T1-weighted/T2-weighted (T1w/T2w) ratio mapping in subcortex. This study provides new insights into the biological basis of subcortical functional hierarchy by revealing the structural and genetic properties of the subcortical functional gradients.

Structural and functional brain correlates of socioeconomic status across the life span: A systematic review

It is well-established that higher socioeconomic status (SES) is associated with improved brain health. However, the effects of SES across different life stages on brain structure and function is still equivocal. In this systematic review, we aimed to synthesise findings from life course neuroimaging studies that investigated the structural and functional brain correlates of SES across the life span. The results indicated that higher SES across different life stages were independently and cumulatively related to neural outcomes typically reflective of greater brain health (e.g., increased cortical thickness, grey matter volume, fractional anisotropy, and network segregation) in adult individuals. The results also demonstrated that the corticolimbic system was most commonly impacted by socioeconomic disadvantages across the life span. This review highlights the importance of taking into account SES across the life span when studying its effects on brain health. It also provides directions for future research including the need for longitudinal and multimodal research that can inform effective policy interventions tailored to specific life stages.

Intergenerational transmission of brain structure and function in humans: a narrative review of designs, methods, and findings

Children often show cognitive and affective traits that are similar to their parents. Although this indicates a transmission of phenotypes from parents to children, little is known about the neural underpinnings of that transmission. Here, we provide a general overview of neuroimaging studies that explore the similarity between parents and children in terms of brain structure and function. We notably discuss the aims, designs, and methods of these so-called intergenerational neuroimaging studies, focusing on two main designs: the parent-child design and the multigenerational design. For each design, we also summarize the major findings, identify the sources of variability between studies, and highlight some limitations and future directions. We argue that the lack of consensus in defining the parent-child transmission of brain structure and function leads to measurement heterogeneity, which is a challenge for future studies. Additionally, multigenerational studies often use measures of family resemblance to estimate the proportion of variance attributed to genetic versus environmental factors, though this estimate is likely inflated given the frequent lack of control for shared environment. Nonetheless, intergenerational neuroimaging studies may still have both clinical and theoretical relevance, not because they currently inform about the etiology of neuromarkers, but rather because they may help identify neuromarkers and test hypotheses about neuromarkers coming from more standard neuroimaging designs.

Mapping pathways to neuronal atrophy in healthy, mid-aged adults: From chronic stress to systemic inflammation to neurodegeneration?

Growing evidence implicates systemic inflammation in the loss of structural brain integrity in natural ageing and disorder development. Chronic stress and glucocorticoid exposure can potentiate inflammatory processes and may also be linked to neuronal atrophy, particularly in the hippocampus and the human neocortex. To improve understanding of emerging maladaptive interactions between stress and inflammation, this study examined evidence for glucocorticoid- and inflammation-mediated neurodegeneration in healthy mid-aged adults. N = 169 healthy adults (mean age = 39.4, 64.5% female) were sampled from the general population in the context of the ReSource Project. Stress, inflammation and neuronal atrophy were quantified using physiological indices of chronic stress (hair cortisol (HCC) and cortisone (HEC) concentration), systemic inflammation (interleukin-6 (IL-6), high-sensitive C-reactive protein (hs-CRP)), the systemic inflammation index (SII), hippocampal volume (HCV) and cortical thickness (CT) in regions of interest. Structural equation models were used to examine evidence for pathways from stress and inflammation to neuronal atrophy. Model fit indices indicated good representation of stress, inflammation, and neurological data through the constructed models (CT model: robust RMSEA = 0.041, robust χ2 = 910.90; HCV model: robust RMSEA <0.001, robust χ2 = 40.95). Among inflammatory indices, only the SII was positively associated with hair cortisol as one indicator of chronic stress (β = 0.18, p < 0.05). Direct and indirect pathways from chronic stress and systemic inflammation to cortical thickness or hippocampal volume were non-significant. In exploratory analysis, the SII was inversely related to mean cortical thickness. Our results emphasize the importance of considering the multidimensionality of systemic inflammation and chronic stress, with various indicators that may represent different aspects of the systemic reaction. We conclude that inflammation and glucocorticoid-mediated neurodegeneration indicated by IL-6 and hs-CRP and HCC and HEC may only emerge during advanced ageing and disorder processes, still the SII could be a promising candidate for detecting associations between inflammation and neurodegeneration in younger and healthy samples. Future work should examine these pathways in prospective longitudinal designs, for which the present investigation serves as a baseline.

Advancements in Non-Invasive Neuroimaging: Exploring the Potential of Radar Technology for Brain Imaging and Tumour Detection

This study investigates radar technology for non-invasive brain imaging and tumor detection, offering an alternative to MRI and CT scans. Using Ansys HFSS to simulate electromagnetic interactions in brain tissues, we evaluate the penetration, signal strength, and safety of Patch and Vivaldi antennas. Results show Patch antennas are optimal for tumor localization, while Vivaldi antennas suit broader scanning applications. Although promising for safer, more accessible imaging, especially in resource-limited environments, further research with diverse models and actual patient data is essential to advance this technology in non-invasive medical diagnostics.