NeuroImage: Clinical

Chronic active lesions (CALs) are a hallmark of multiple sclerosis (MS) pathology, associated with extensive tissue damage, disability progression, and overall disease burden. Histopathologically, they consist of a hypocellular core surrounded by a rim of iron-laden, chronically activated microglia/macrophages. Proposed magnetic resonance imaging (MRI) biomarkers of CALs are paramagnetic rim lesions (PRLs) or slowly expanding lesions (SELs), detected respectively on susceptibility-based images or on longitudinal conventional MRI. While PRLs are histopathologically validated in vivo correlates of CALs, SELs lack pathological validation. In this study, we examine the relationship between SELs and PRLs and evaluate the robustness of the SEL detection algorithm in 56 MS participants, all imaged using a strictly homogeneous protocol on the same 3T scanner for three consecutive timepoints. PRLs included distinct subgroups of both shrinking and expanding lesions (p < 0.001), challenging the assumption that CALs necessarily expand over time. SEL detection demonstrated instability across different input resolution and segmentation methods, yielding a mean dice similarity score of 0.375. In random forest analysis, SEL volume showed inconsistent and weaker predictive value for MS disability and severity (EDSS, MSSS) compared to PRL volume. Critically, lesion-level overlap between SELs and PRLs was negligible (Cohens {kappa} = -0.022) once corrected for overlap by chance. Taken together, our findings indicate that SELs and PRLs are essentially independent, underscoring the need for a refined longitudinal volumetric definition to establish a reliable CALs biomarker.

IntroductionGenome Wide Association Studies (GWAS) revealed the highly polygenic architecture of Attention-Deficit/Hyperactivity Disorder (ADHD) and highlighted the contribution of common variants related to brain development and function. In parallel, several imaging studies attempted to discover disorder-related brain structures, with some significant findings concerning white matter. Two-sample mendelian randomization (2SMR) is a powerful tool to evaluate causality between two phenotypes using summary statistics data. We aimed to investigate a possible causal relationship between white matter genetically predicted variation and ADHD diagnosis through 2SMR. MethodsA unidirectional two-sample MR analysis was performed based on summary statistics of GWAS between 22 different white matter (WM) mean fractional anisotropy measures and ADHD. We used 4 different MR approaches, considering IVW random effects as the main analysis, followed by several sensitivity analyses. Linkage Disequilibrium Score Regression (LDSC) was evaluated in the same set of samples to corroborate the direction of associations. Results and DiscussionOur most consistent finding across MR and LDSC approach, following the sensitivity analyses, indicate that the decreased WM microstructure integrity of the fornix stria terminalis (FXSTivw beta:-0.266 SE:0.083 pFDR: 0.021) genetic liability has a causal influence on ADHD diagnosis. The FXST is formed by connection fibers inside the limbic system, which is crucial to emotional processing, learning, and memory, functions usually impaired in ADHD. Therefore, this study increases knowledge concerning ADHD neurobiology and provides novel evidence of the causal effect of WM integrity in the limbic system, which could contribute to the advances in additional diagnostic tools as well as pharmacological brain structure targets.

Premature birth occurs during a phase of intense brain maturation, making white matter (WM) particularly vulnerable to injury. Beyond major lesions, subtle and widespread microstructural alterations also contribute to later neurodevelopmental impairments. We aimed to characterize the impact of key clinical risk factors on global and tract-specific WM microstructure at term-equivalent age (TEA), using 3T-diffusion-MRI data of 111 infants born before 33 weeks of gestation. We developed a lesion-robust tractography pipeline suitable for heterogeneous neonatal anatomy and extracted diffusion tensor imaging (DTI) metrics in sensorimotor tracts: corticospinal tract (CST), superior thalamic radiation (STR), frontal aslant tract (FAT), forceps minor (FMI) and middle cerebellar peduncle (MCP). Associations with risk factors were assessed accounting for age at MRI or global WM microstructure. Tractography succeeded in most infants despite marked anatomical variability and/or overt lesions. Being a male, small for gestational age (SGA) at birth, encountering sepsis and having severe Kidokoro radiological score for WM were associated with altered global WM metrics. At the tract level, CST and STR showed the strongest susceptibility to SGA, prolonged parenteral nutrition, and Kidokoro score. In contrast, for FAT, associations with extreme prematurity, SGA and invasive ventilation were contrary to the expected direction, after adjustment for global WM microstructure. Findings were partially replicated in infants without macroscopic abnormalities, supporting the presence of WM dysmaturation even in the absence of visible injury. DTI metrics thus provide tract-specific biomarkers of early WM microstructure in preterm infants, which are sensitive to risk factors and could inform targeted prevention and intervention.

A cardinal feature of the encephalopathy of prematurity is dysmaturation of developing white matter and subsequent hypomyelination. Magnetisation transfer imaging (MTI) offers surrogate markers for myelination including magnetisation transfer ratio (MTR) and magnetisation transfer saturation (MTsat). Using data from 105 neonates, we characterise MTR and MTsat in the developing brain and investigate how these markers are affected by gestational age at scan and preterm birth. We explore correlations of the two measures with fractional anisotropy (FA), radial diffusivity (RD) and T1w/T2w ratio which are commonly used markers of white matter integrity in early life. We used two complementary analysis methods: voxel-wise analysis across the white matter skeleton, and tract-of-interest analysis across 16 major white matter tracts. We found that MTR and MTsat positively correlate with gestational age at scan. Preterm infants at term-equivalent age had lower values of MTsat in the genu and splenium of the corpus callosum, while MTR was higher in central white matter regions, the corticospinal tract and the uncinate fasciculus. Correlations of MTI metrics with other MRI parameters revealed that there were moderate positive correlations between T1w/T2w and MTsat and MTR at voxel-level, but at tract-level FA had stronger positive correlations with these metrics. RD had the strongest correlations with MTI metrics, particularly with MTsat in major white matter tracts. The observed changes in MTI metrics are consistent with an increase in myelin density during early postnatal life, and lower myelination and cellular/axonal density in preterm infants at term-equivalent age compared to term controls. Furthermore, correlations between MTI-derived features and conventional measures from dMRI provide new understanding about the contribution of myelination to non-specific imaging metrics that are often used to characterise early brain development.

BackgroundCorpus callosum anomalies are commonly noted in autism spectrum disorder (ASD). Given the complexity of its microstructural architecture, with crossing fibers projecting throughout, we applied fixel-based analysis to probe white matter micro- and macrostructure within this region. As ASD is a neurodevelopmental condition with noted abnormalities in brain growth, age was also investigated. MethodsData for participants with (N=54) and without (N=50) ASD, aged 5-34 years, were obtained from the Autism Brain Imaging Data Exchange-II (ABIDE-II). Within each site, indices of fiber density (FD), fiber cross-section (FC), and combined fiber density and cross-section (FDC) were compared between those groups. ResultsYoung adolescents with ASD (age = 11.19 {+/-} 7.54) showed reduced macroscopic FC and FDC compared to age-matched neurotypical controls (age = 10.04 {+/-} 4.40). Reduced FD and FDC was noted in a marginally older ASD (age 13.87 {+/-} 3.15) cohort compared to matched controls (age = 13.85 {+/-} 2.90). Among the oldest cohorts, a non-significant trend indicated reduced FD in older adolescents/young adults with ASD (age = 17.07 {+/-} 3.56) compared to controls (age = 16.55 {+/-} 2.95). There was a positive correlation between age and callosal mean FC and FDC in the youngest cohort. When stratified by diagnosis, this finding remained only for the ASD sample. ConclusionWhite matter aberration appears greatest among younger ASD cohorts. In older adolescents and young adults, less of the corpus callosum seems affected. This supports the suggestion that some early neuropathophysiological indicators in ASD may dissipate with age.

Magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy in essential tremor (ET) targets the ventral intermediate nucleus hub region within the cerebello-thalamo-cortical tract (CTCT). Understanding the microstructural changes in the CTCT over time and their link to tremor improvement is crucial from a tremor-network perspective. We retrospectively analyzed tremor scores, lesion characteristics, and diffusion MRI-derived CTCT microstructural measures in 27 ET patients pre-treatment (T0), at 1 month (T2), and 6 months (T3) post-MRgFUS. Using probabilistic tractography, we created an average CTCT mask for assessing fractional anisotropy (FA), axial (AD), mean (MD), and radial diffusivity (RD) measures across time points. Significant tremor reduction was observed at T2 and T3. The Linear mixed effect analyses showed significant time effects for FA, MD, and AD. Relative to baseline, post-hoc comparisons showed a significant decrease of FA and AD at lesion site only for T2. Instead, there was a significant increase in AD and MD at T3 compared to T2 at lesion site, and remotely near the motor cortex. Lesion size and FA changes in the CTCT at T2 showed only trend-level correlations with tremor outcome. Stronger associations were observed for the thalamic lesion-tract overlap at T2, which were even more robust at T3. Dynamic microstructural changes suggest early axonal disruption at the lesion site and subsequent reorganization, with remote CTCT changes potentially indicating chronic degeneration. Meanwhile, microstructural measures show limited predictive value for longer-term tremor outcome compared with macroanatomical lesion-CTCT overlap. Yet, advanced diffusion imaging protocol could increase the sensitivity to predict MRgFUS clinical outcome.

White matter hyperintensities (WMH) are a highly prevalent finding on FLAIR MRI scans and a prominent feature of white matter pathology across cerebrovascular and neurodegenerative diseases. Currently, WMH are assessed with visual rating scales such as the Fazekas scale or with their volume, as calculated from automatic or manual segmentations. Both methods have limitations: Visual rating scales are rater-dependent and coarse, while WMH volume does not take the confluence of lesions into account and thus disregards their spatial organisation. As an alternative, here we propose a novel automated method for quantifying the confluence of white matter hyperintensities on a continuous standardised scale between 0 and 1. The metric is based on WMH segmentations from routine MRI and quantifies the extent to which individual WMH merge into coherent lesions, independently of total lesion volume. We apply the method to QMIN-MC, a large UK memory clinic cohort, and show associations of the confluence metric with age, cognitive performance across domains, and Fazekas ratings. Participants with vascular and mixed dementia showed higher confluence than other diagnostic groups, whereas cognitively unimpaired participants showed lower confluence. However, confluence did not explain additional cognitive variance after accounting for log-transformed WMH volume. Findings were validated in DELCODE, an independent cohort of individuals with neurodegenerative disorders, replicating our original results. In this validation cohort, periventricular WMH confluence remained associated with cognition after adjustment for WMH volume. These findings introduce WMH confluence as a reproducible, automated, and fine-grained measure of lesion spatial organisation. It provides complementary information about morphological WMH severity beyond volume and is an alternative to visual rating scales. Although related to WMH volume in memory-clinic populations, confluence captures clinically interpretable information and may complement existing WMH measures for improved lesion characterisation in studies of white matter disease, ageing, and cognitive impairment.

BackgroundAlthough observational studies indicate a complex, bidirectional association between major depressive disorder (MDD) and cerebral small vessel disease (CSVD), the results are frequently inconsistent. This study investigated the potential correlation of MDD with both CSVD clinical outcomes and imaging markers, utilizing a bidirectional Mendelian randomization (MR) study design. MethodsInstrumental variables for both MDD and CSVD were extracted from the latest or most extensive genome-wide association study (GWAS) data available for each phenotype. Clinical outcomes and imaging markers of CSVD were defined using several parameters. The inverse variance weighting (IVW) method with additional sensitivity and heterogeneity analyses was used. Furthermore, a separate GWAS for depression was used to validate our significant findings. ResultsIn the forward MR analyses, the genetically predicted risk of MDD was positively associated with two CSVD phenotypes showing microscopic white matter (WM) damage: mean diffusivity (IVW OR = 2.191, 95 % CI 1.226 to 3.917, p = 0.008) and WM-enlarged perivascular space (OR = 1.053 95 % CI 1.006 to 1.101, p = 0.026). The use of an independent database for depression yielded no significant risk of depression associated with these two CSVD traits. Furthermore, reverse MR analyses showed no evidence of reverse causality between MDD and an altered CSVD risk. ConclusionsThis study utilizing MR imaging findings supports a substantial causal association between MDD and CSVD-related indicators of impaired WM microstructure. It is necessary to exercise caution when extending these results to individuals with depression.

An inflammatory subtype of major depressive disorder (MDD) is associated with treatment resistance pointing to an unmet need for adjunctive treatments. To evaluate treatment-related changes in brain inflammation, diffusion basis spectrum imaging (DBSI) is a promising non-radiation-based technique for longitudinal designs which has been verified with histopathology. However, its use as an endpoint in clinical trials is dependent on its individual-level reliability to robustly track changes. Here, we evaluated two DBSI runs acquired in 94 participants (including 43 participants with MDD) on the same day about 1.5 h apart to assess short-term test-retest reliability. Fiber fraction (reflecting axonal/dendrite density) and hindered fraction (reflecting edema) showed moderate to high test-retest reliability in both gray and white matter regions, whereas restricted fraction (reflecting cellularity) showed lower values in gray and white matter. Group-level reliability was similar in participants with MDD, except for lower reliability of hindered fraction in gray matter. Re-identification rates of individual brain maps were higher using voxel-level white matter signatures compared to gray matter regions of interest (ROIs) (p<.001). Crucially, participants with MDD showed reduced fiber fraction (tmax=4.68, k=38) and elevated hindered fraction (tmax=4.74, k=32) in the cingulate bundle, consistent with increased white matter inflammation, while gray matter ROI-based classification failed to identify cases. We conclude that DBSI is a promising technique to track inflammatory signatures in MDD, particularly in white matter tracts. Since several frontal and subcortical gray matter ROIs showed insufficient reliability, their assessment would require multiple DBSI runs to provide robust estimates.

Traumatic brain injury (TBI) is a risk factor for neurodegeneration and cognitive decline, yet the underlying pathophysiologic mechanisms are incompletely understood. This gap in knowledge is in part related to a lack of reliable and efficient methods for measuring cortical lesions in neuroimaging studies. The objective of this study was to develop a semi-automated lesion detection tool and apply it to an investigation of longitudinal changes in brain structure among individuals with chronic TBI. We identified 24 individuals with chronic moderate-to-severe TBI enrolled in the Late Effects of TBI (LETBI) study who had cortical lesions detected by T1-weighted MRI and underwent two MRI scans at least two years apart. Initial MRI scans were performed more than one year post-injury, and follow-up scans were performed 3.1 (IQR=1.7) years later. We leveraged FreeSurfer parcellations of T1-weighted MRI volumes and a recently developed super-resolution technique, SynthSR, to automate the identification of cortical lesions in this longitudinal dataset. Trained raters received the data in a randomized order and manually edited the automated lesion segmentations, yielding a final semi-automated lesion mask for each scan at each time point. Inter-rater variability was assessed in an independent cohort of 10 additional LETBI subjects with cortical lesions. The semi-automated lesion segmentations showed a high level of accuracy compared to "ground truth" lesion segmentations performed via manual segmentation by a separate blinded rater. In a longitudinal analysis of the semi-automated segmentations, lesion volume increased between the two time points with a median volume change of 4.91 (IQR=12.95) mL (p<0.0001). Lesion volume significantly expanded in 40 of 61 measured lesions (65.6%), as defined by a longitudinal volume increase that exceeded inter-rater variability. Longitudinal analyses showed similar changes in lesion volume using the ground-truth lesion segmentations. Inter-scan duration was not associated with the magnitude of lesion growth. Reliable and efficient semi-automated lesion segmentation is feasible in studies of chronic TBI, creating opportunities to elucidate mechanisms of post-traumatic neurodegeneration.

Stroke recovery outcomes vary across individuals, motivating the search for biomarkers that can improve prediction. White matter hyperintensities (WMH) volume is a leading biomarker candidate, with FLAIR MRI typically used for WMH segmentation; however, T1-weighted (T1) MRI is often more available. Therefore, we evaluated the performance of two automated WMH segmentation methods (WMH-SynthSeg and SAMSEG) to determine whether WMH volume can be reliably estimated using T1 alone. We analyzed imaging data from 227 stroke patients across three datasets spanning early subacute to chronic recovery, each with gold-standard WMH masks and stroke lesion masks manually traced on available T1 and FLAIR scans. WMH was segmented using T1 only as input to WMH-SynthSeg and SAMSEG, as well as using both T1 and FLAIR as input to SAMSEG, as previously implemented in stroke recovery research. Automated WMH segmentations were compared to the gold-standard WMH mask: accuracy was assessed using Dice similarity index (SI) and cluster-level false negative ratio, while agreement was assessed using intraclass correlation, Pearsons correlation, and volume ratio. We used linear mixed-effects models to evaluate whether SI was influenced by factors such as WMH volume, stroke lesion volume, WMH contrast, age, sex, and days since stroke, with dataset as a random effect. WMH-SynthSeg using T1-only input produced more accurate and reliable WMH segmentations compared to SAMSEG with T1-only input and performed comparably to SAMSEG using both T1 and FLAIR input. WMH-SynthSeg using T1-only input may be used for WMH volume estimation in stroke recovery research in the absence of multimodal imaging. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/25338564v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@4f3587org.highwire.dtl.DTLVardef@434ff9org.highwire.dtl.DTLVardef@137780forg.highwire.dtl.DTLVardef@ab2790_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- WMH volume, often assessed via multimodal imaging, predicts post-stroke outcomes - T1-only methods would facilitate WMH analysis if multimodal MRI is unavailable - It is unclear how T1-only methods perform in brains with stroke lesions - We show T1-based WMH-SynthSeg estimates strongly agree with gold standard methods - Accuracy was stable across stroke lesion sizes but varied with WMH volume/contrast

Approximately 65% of moderate-to-severe traumatic brain injury (m-sTBI) patients present with poor long-term behavioural outcomes, which can significantly impair activities of daily living. Numerous diffusion-weighted MRI studies have linked these poor outcomes to decreased white matter integrity of several commissural tracts, association fibres and projection fibres in the brain. However, these studies focused on group-based analyses, which are unable to deal with the substantial between-patient heterogeneity in m-sTBI. As a result, there is increasing interest in conducting individualised neuroimaging analyses. Here, we generated a detailed subject-specific characterisation of microstructural organisation of white matter tracts in 5 chronic patients with m-sTBI (29 - 49y, 2 females). We developed an imaging analysis framework using fixel-based analysis and TractLearn to determine whether the values of fibre density of white matter tracts at the individual patient level deviate from the healthy control group (n = 12, 8F, Mage=35.7y, age range 25 - 64y). Our individualised analysis confirmed unique white matter profiles, and the heterogeneous nature of m-sTBI to properly characterise the extent of brain abnormality. Future studies incorporating clinical data, as well as utilising larger reference samples and examining the test-retest reliability of the fixel-wise metrics are warranted. This proof-of-concept study suggests that these resulting individual profiles may assist clinicians in planning personalised training programs for chronic m-sTBI patients, which is necessary to achieve optimal behavioural outcomes and improved quality of life.

BackgroundAberrant myelination represents a critical but understudied mechanism in cognitive difficulties associated with neurodevelopmental conditions. Neurofibromatosis 1 (NF1), provides a unique monogenic model to investigate this relationship, as white matter abnormalities are consistently observed, yet their microstructural basis remains uncharacterized. We present the first dual-modality quantitative myelin mapping study in NF1, employing Magnetization Transfer and T1W/T2W ratio imaging to delineate regional myelin alterations. Methods and materialsWe conducted a case-control study of 78 children (58 NF1 and 20 neurotypical controls, ages 11-18 years). Magnetization Transfer Ratio (MTR) and T1-weighted/T2-weighted (T1W/T2W) ratio imaging were used to quantify regional myelin properties. Working memory was assessed using the visuospatial n-back task. ResultsCompared to controls, children with NF1 showed significant myelin reductions in the thalamus, basal ganglia and cerebellum, converging across both imaging modalities. These deficits persisted independent of T2 hyperintensities, indicating a primary myelin pathology. Regional myelin alterations did not correlate with working memory performance. ConclusionThis is the first study to employ two simultaneous methods to characterise myelin differences in NF1. The findings indicate that NF1-related myelin deficits are predominantly confined to the brainstem, cerebellar, and diencephalic structures. These results provide a neurobiological framework for understanding white matter pathology in NF1 and may help guide therapeutic strategies targeting myelination deficits in this disorder.

ObjectiveTo investigate the metabolic pattern of different types of iron accumulation in multiple sclerosis (MS) lesions, and compare metabolic alterations within and at the periphery of lesions and newly emerging lesions in vivo according to iron deposition. Methods7T MR spectroscopic imaging and susceptibility-weighted imaging was performed in 31 patients with relapsing-remitting MS (16 female/15 male; mean age, 36.9 {+/-} 10.3 years). Mean metabolic ratios of four neuro-metabolites were calculated for regions of interest (ROI) of normal appearing white matter (NAWM), "non-iron" (lesion without iron accumulation on SWI), and three distinct types of iron-laden lesions ("rim": distinct rim-shaped iron accumulation; "area": iron deposition across the entire lesions; "transition": transition between "area" and "rim" accumulation shape), and for lesion layers of "non-iron" and "rim" lesions. Furthermore, newly emerging "non-iron" and "iron" lesions were compared longitudinally, as measured before their appearance and one year later. ResultsThirty-nine of 75 iron-containing lesions showed no distinct paramagnetic rim. Of these, "area" lesions exhibited a 65% higher mIns/tNAA (p=0.035) than "rim" lesions. Comparing lesion layers of both "non-iron" and "rim" lesions, a steeper metabolic gradient of mIns/tNAA ("non-iron" +15%, "rim" +40%) and tNAA/tCr ("non-iron" -15%, "rim" -35%) was found in "iron" lesions, with the lesion core showing +22% higher mIns/tNAA (p=0.005) and -23% lower tNAA/tCr (p=0.048) in "iron" compared to "non-iron" lesions. In newly emerging lesions, 18 of 39 showed iron accumulation, with the drop in tNAA/tCr after lesion formation remaining significantly lower compared to pre-lesional tissue over time in "iron" lesions (year 0: p=0.013, year 1: p=0.041) as opposed to "non-iron" lesions (year 0: p=0.022, year 1: p=0.231). Conclusion7T MRSI allows in vivo characterization of different iron accumulation types each presenting with a distinct metabolic profile. Furthermore, the larger extent of neuronal damage in lesions with a distinct iron rim was reconfirmed via reduced tNAA/tCr concentrations, but with metabolic differences in lesion development between (non)-iron-containing lesions. This highlights the ability of MRSI to further investigate different types of iron accumulation and suggests possible implications for disease monitoring. Key pointsO_LIIron-containing lesions were suggested as a biomarker for tissue damage, a more aggressive disease course, and worse clinical outcome, but related metabolic alterations are poorly understood. C_LIO_LIOur MRSI results confirm a higher extent of tissue damage within paramagnetic rim lesions reflected by reduced tNAA/tCr. Forty-six percent of newly emerging lesions showed an iron accumulation, correlating with an altered metabolic behavior compared to non-iron lesions. C_LIO_LIOnly forty-eight percent of iron-containing lesions have a distinct rim-shaped iron accumulation, although most studies focus on these paramagnetic rim lesions. Our results show highly different metabolic profiles (especially with regard to mIns/tNAA and tNAA/tCr) within different iron accumulation types, highlighting the need for distinct classification of iron accumulation in future studies. C_LI

Pediatric-onset multiple sclerosis (POMS) involves aggressive inflammation and large lesions; however, its detailed shapes and structures remain poorly understood. Traditional volumetric metrics often overlook the complex geometry of these lesions. The main objective of this study is to develop a differential geometry-based framework to quantify the shape and structure of lesions in pediatric multiple sclerosis(MS) patients using longitudinal 3D FLAIR MRI. The goal was to identify reproducible lesion morphotypes and to track their evolution over time. Our approach sensitively tracked shape changes over time and revealed consistent progression patterns. Our findings suggest that geometric biomarkers offer a powerful new lens for decoding MS heterogeneity and tracking disease activity in the pediatric population.

Background: Prior neuroimaging suggests brain differences between children with attention deficit hyperactivity disorder due to prenatal alcohol exposure (ADHD+PAE) and non-exposed children with ADHD due to other, e.g., familial, causes (ADHD-PAE). There has been interest in regional brain levels of ;gamma-aminobutyric acid (GABA) and glutamate (Glu) measured in vivo with magnetic resonance spectroscopy (MRS) as possible indicators of local inhibitory, respectively, excitatory activity in ADHD. For the first time, we report here a comparison of GABA and Glu in ADHD+PAE vs. ADHD-PAE. Methods: At 3 T, we used J-difference-edited single-voxel MRS to assay GABA and Glu in 28 children with ADHD+PAE, 20 with ADHD-PAE, and 28 typically developing (TD) controls, all aged 8-14 years. MRS was sampled from midline anterior middle cingulate cortex (aMCC), the cognitive cingulate considered functionally relevant to ADHD. Spectra were fit with custom software, including a unique technique for isolating the GABA signal from the confounding macromolecular baseline (MMBL). Results: aMCC GABA was higher in ADHD+PAE and ADHD-PAE than in TD. GABA increased with age in TD, but not in ADHD+PAE or ADHD-PAE. Similar effects were observed for the ratios GABA/Glu and GABA/Glx. For GABA+MMBL (GABA+) these effects were not seen, rather GABA+ and MMBL increased with age for the ADHD+PAE group only. No significant effects were found for Glu or Glx. Conclusions: GABA in the aMCC does not distinguish the two etiologies of ADHD, rather elevated GABA that follows an abnormal developmental appears to be common to both. High GABA may reflect increased inhibition of the aMCC impairing its cognitive functions. GABA+ results in ADHD may not tract reliably with underlying GABA values. Negative results for Glu and Glx should be reexamined at shorter echo-times.

Low-grade systemic inflammation is linked to cardiometabolic diseases and increased cardiovascular risk. Patients with mood disorders, such as Major Depressive Disorder (MDD) and Bipolar Disorder (BD), also show elevated cardiovascular risk and inflammatory markers, suggesting shared biological pathways between mood and cardiometabolic conditions. The kynurenine (KYN) pathway, activated by inflammatory cytokines and involved in neurotransmitter systems linked to mood, provides a promising area to explore inflammatory-related genetic overlaps in these disorders, with increasing interest in the SH2B3 rs3184504 SNP. Imaging markers like white matter hyperintensities (WMHs) and white matter (WM) microstructure alterations are associated with mood and cardiovascular disorders. This study aimed to investigate the genetic load link to KYN levels, such as KYN polygenic risk score (PRS) and its effect on white matter hyperintensities (WMHs), outcomes of presumed vascular suffering, and WM microstructure in a sample of 95 MDD and 80 BD patients. Higher PRS for KYN was associated with increased circulating KYN levels and KYN/TRP ratio. KYN PRS predicted the presence of WMHs. The SH2B3 rs3184504 T variant was associated with increased PRS for KYN and a higher number of WMHs. KYN levels and KYN/TRP ratio were not associated with WMHs, while KYN PRS positively correlated with higher axial (AD) and mean diffusivity (MD), with a nominal significance for radial diffusivity (RD). The findings support a genetic contribution to elevated KYN and WM integrity alterations in mood disorders. PRS for KYN indicates a potential predisposition to inflammatory and vascular dysregulation, and SH2B3 rs3184504 may modulate this risk.

BackgroundIn multiple sclerosis (MS), demyelination and degeneration of transcallosal pathways impair interhemispheric communication. While white matter damage is well documented, the impact of cortical lesions on transcallosal conduction remains unclear. ObjectiveTo determine whether cortical lesions in the sensorimotor hand area (SM1{square}HAND) contribute to impaired transcallosal motor interaction using ultra{square}high{square}field MRI and transcranial magnetic stimulation (TMS). MethodsTwenty healthy controls (HCs) and 38 MS patients underwent 7T structural and diffusion{square}weighted MRI. Structural scans were used to identify cortical lesions in SM1{square}HAND, while diffusion tensor imaging (DTI) quantified microstructural properties in the transcallosal tract connecting left and right SM1{square}HAND. Single{square}pulse TMS was delivered to each SM1{square}HAND during tonic first dorsal interosseous contraction to measure the ipsilateral silent period (iSP). Corticospinal conduction was measured with contralateral motor{square}evoked potentials (MEPs), while the iSP was used to compute transcallosal conduction time (TCT). ResultsAmong MS patients, 41 of 76 hemispheres contained an SM1{square}HAND lesion. TCT was significantly prolonged in MS relative to HCs (P<0.001). In patients, cortical lesions delayed transcallosal conduction from the non{square}lesion{square}bearing to the lesion{square}bearing hemisphere (P=0.026). This direction-specific delay was associated with an intracortical lesion type (P<0.001), but not with DTI{square}derived microstructural measures (P>0.05). ConclusionsThe presence of cortical lesions in the sensorimotor cortex affects transcallosal inhibition between homologous sensorimotor regions in MS, slowing the build-up of inhibitory influence on the corticospinal output in the lesioned cortex. This delayed inhibitory buildlup appears to be associated with an intracortical lesion type. HighlightsO_LIIpsilateral silent period reveals delayed transcallosal motor interaction in multiple sclerosis C_LIO_LICortical lesions in sensorimotor cortex delay the onset of transcallosal motor inhibition C_LIO_LIDelayed transcallosal inhibition is only present toward the lesioned cortex C_LIO_LIIntracortical lesions, not callosal microstructure, is linked to this directionlspecific delay C_LI

BackgroundThe neurobiological underpinnings of the characteristically higher intra-individual variability of reaction times (IIVRT) in patients with ADHD remain poorly understood. The aim of the current study was to characterize the role of the default mode and other canonical brain networks measured by functional magnetic resonance imaging (fMRI) to task performance fluctuations measured by IIVRT. To our knowledge, no prior fMRI study has shown the involvement of posterior default mode network (DMN) in ADHD IIVRT. We expected that moment-to-moment fluctuations in hemodynamic responses in posterior DMN would predict higher IIVRT in ADHD. MethodsAdolescents (12 to 19 years old) with ADHD (n= 55) and healthy controls (n= 55) performed a fMRI Go/NoGo task. Whole-brain independent component analysis (ICA) segregated hemodynamic responses into functional brain networks, then further decomposed into individual trial-specific estimates of hemodynamic response amplitude. Mean and variability metrics of these amplitudes were tested in stepwise linear regression analyses to identify which functional brain networks predicted high IIVRT. ResultsAs hypothesized, variability in hemodynamic responses in posterior DMN regions predicted level of IIVRT. In posterior cingulate cortex this variability predicted higher IIVRT only in ADHD, whereas in precuneus variability in hemodynamic responses predicted lower IIVRT. Average hemodynamic responses in a bilateral superior temporal cortex network predicted higher IIVRT only in ADHD. ConclusionOur findings suggest that estimating variability in hemodynamic responses is crucial to understand the involvement of the intrinsic default mode in attentional lapses in ADHD. The parcellation into subnetworks showed the differentiating role of default mode in attentional lapses in ADHD.

Deep brain stimulation (DBS) is being investigated as treatment for patients with refractory major depressive disorder (MDD). However, little is known about how DBS exerts its antidepressive effects. Here, we investigated whether ventral anterior limb of the internal capsule (vALIC) stimulation modulates a limbic network centered around the amygdala in patients with treatment resistant MDD. Nine patients underwent resting state functional magnetic resonance imaging (fMRI) before DBS surgery and after one year of treatment. In addition, they were scanned twice within two weeks during the subsequent double blind crossover phase with active and sham treatment. Eleven matched controls underwent fMRI scans at same time intervals to account for test-retest effects. The imaging data was investigated with functional connectivity analysis and dynamic causal modelling (DCM). Results showed that one year of DBS treatment was associated with increased functional connectivity of the left amygdala with precentral cortex and left insula along with decreased bilateral connectivity between nucleus accumbens and ventromedial prefrontal cortex. No changes in functional connectivity were observed during the crossover phase. Effective connectivity analyses using DCM revealed widespread amygdala-centric changes between pre-surgery and one year follow-up, while the crossover phase was associated with insula-centric changes between active and sham stimulation. These results suggest that vALIC DBS results in complex rebalancing of the limbic network involved in emotion, reward and interoceptive processing.