Prescription Opioids and Brain Structure in Community-Dwelling Older Adults.

OBJECTIVE: To evaluate the associations between prescription opioid exposures in community-dwelling older adults and gray and white matter structure by magnetic resonance imaging. METHODS: Secondary analysis was conducted of a prospective, longitudinal population-based cohort study employing cross-sectional imaging of older adult (≥65 years) enrollees between November 1, 2004, and December 31, 2017. Gray matter outcomes included cortical thickness in 41 structures and subcortical volumes in 6 structures. White matter outcomes included fractional anisotropy in 40 tracts and global white matter hyperintensity volumes. The primary exposure was prescription opioid availability expressed as the per-year rate of opioid days preceding magnetic resonance imaging, with a secondary exposure of per-year total morphine milligram equivalents (MME). Multivariable models assessed associations between opioid exposures and brain structures. RESULTS: The study included 2185 participants; median (interquartile range) age was 80 (75 to 85) years, 47% were women, and 1246 (57%) received opioids. No significant associations were found between opioids and gray matter. Increased opioid days and MME were associated with decreased white matter fractional anisotropy in 15 (38%) and 16 (40%) regions, respectively, including the corpus callosum, posterior thalamic radiation, and anterior limb of the internal capsule, among others. Opioid days and MME were also associated with greater white matter hyperintensity volume (1.02 [95% CI, 1.002 to 1.036; P=.029] and 1.01 [1.001 to 1.024; P=.032] increase in the geometric mean, respectively). CONCLUSION: The duration and dose of prescription opioids were associated with decreased white matter integrity but not with gray matter structure. Future studies with longitudinal imaging and clinical correlation are warranted to further evaluate these relationships.

Diffusion-tensor-imaging 1-year-old and 2-year-old infant brain atlases with comprehensive gray and white matter labels.

Human infancy is marked by fastest postnatal brain structural changes. It also coincides with the onset of many neurodevelopmental disorders. Atlas-based automated structure labeling has been widely used for analyzing various neuroimaging data. However, the relatively large and nonlinear neuroanatomical differences between infant and adult brains can lead to significant offsets of the labeled structures in infant brains when adult brain atlas is used. Age-specific 1- and 2-year-old brain atlases covering all major gray and white matter (GM and WM) structures with diffusion tensor imaging (DTI) and structural MRI are critical for precision medicine for infant population yet have not been established. In this study, high-quality DTI and structural MRI data were obtained from 50 healthy children to build up three-dimensional age-specific 1- and 2-year-old brain templates and atlases. Age-specific templates include a single-subject template as well as two population-averaged templates from linear and nonlinear transformation, respectively. Each age-specific atlas consists of 124 comprehensively labeled major GM and WM structures, including 52 cerebral cortical, 10 deep GM, 40 WM, and 22 brainstem and cerebellar structures. When combined with appropriate registration methods, the established atlases can be used for highly accurate automatic labeling of any given infant brain MRI. We demonstrated that one can automatically and effectively delineate deep WM microstructural development from 3 to 38 months by using these age-specific atlases. These established 1- and 2-year-old infant brain DTI atlases can advance our understanding of typical brain development and serve as clinical anatomical references for brain disorders during infancy.

Inhibition of ADORA3 promotes microglial phagocytosis and alleviates chronic ischemic white matter injury.

BACKGROUND: Adenosine A3 receptor (ADORA3) belongs to the adenosine receptor families and the role of ADORA3 in vascular dementia (VaD) is largely unexplored. The present study sought to determine the therapeutic role of ADORA3 antagonist in a mouse model of VaD. METHODS: The GSE122063 dataset was selected to screen the differential expression genes and pathways between VaD patients and controls. A mouse model of bilateral carotid artery stenosis (BCAS) was established. The cognitive functions were examined by the novel object recognition test, Y maze test, and fear of conditioning test. The white matter injury (WMI) was examined by 9.4 T MRI, western blot, and immunofluorescence staining. The mechanisms of ADORA3-regulated phagocytosis by microglia were examined using qPCR, western blot, dual immunofluorescence staining, and flow cytometry. RESULTS: The expression of ADORA3 was elevated in brain tissues of VaD patients and ADORA3 was indicated as a key gene for VaD in the GSE122063. In BCAS mice, the expression of ADORA3 was predominantly elevated in microglia in the corpus callosum. ADORA3 antagonist promotes microglial phagocytosis to myelin debris by facilitating cAMP/PKA/p-CREB pathway and thereby ameliorates WMI and cognitive impairment in BCAS mice. The therapeutic effect of ADORA3 antagonist was partially reversed by the inhibition of the cAMP/PKA pathway. CONCLUSIONS: ADORA3 antagonist alleviates chronic ischemic WMI by modulating myelin clearance of microglia, which may be a potential therapeutic target for the treatment of VaD.

Migraine or any headaches and white matter hyperintensities and their progression in women and men.

BACKGROUND: Cross-sectional and longitudinal studies have been conducted to investigate the association between migraine and any headache and white matter hyperintensities (WMH). However, studies are inconsistent regarding the strength of the association and its clinical significance. The aim of our study was to investigate the association between headache and its subtypes (migraine with aura (MigA+), migraine without aura (MigA-), non-migraine headache (nonMigHA)) and WMH and its course in the population-based 1000BRAINS study using state-of-the-art imaging techniques and migraine classification according to modified international classification of headache disorders. METHODS: Data from 1062 participants (45% women, 60.9 ± 13.0 years) with ever or never headache (neverHA) and complete quantitative (WMH volume) and qualitative (Fazekas classification) WMH data at first imaging and after 3.7 ± 0.7 years (393 participants) were analyzed. The sex-specific association between headache and its subtypes and WMH volume and its change was evaluated by linear regression, between headache and its subtypes and Fazekas score high vs. low (2-3 vs. 0-1) by log-binomial regression, adjusted for confounders. RESULTS: The lifetime prevalence of headache was 77.5% (10.5% MigA+, 26.9% MigA-, 40.1% nonMigHA). The median WMH volume was 4005 (IQR: 2454-6880) mm3 in women and 4812 (2842-8445) mm3 in men. Women with any headaches (all headache types combined) had a 1.23 [1.04; 1.45]-fold higher WMH volume than women who reported never having had a headache. There was no indication of higher Fazekas grading or more WMH progression in women with migraine or any headaches. Men with migraine or any headaches did not have more WMH or WMH progression compared to men without migraine or men who never had headache. CONCLUSIONS: Our study demonstrated no increased occurrence or progression of WMH in participants with mgiraine. But, our results provide some evidence of greater WMH volume in women with headache of any type including migraine. The underlying pathomechanisms and the reasons why this was not shown in men are unclear and require further research.

Physiological aging and inflammation-induced cellular senescence may contribute to oligodendroglial dysfunction in MS.

Aging affects all cell types in the CNS and plays an important role in CNS diseases. However, the underlying molecular mechanisms driving these age-associated changes and their contribution to diseases are only poorly understood. The white matter in the aging brain as well as in diseases, such as Multiple sclerosis is characterized by subtle abnormalities in myelin sheaths and paranodes, suggesting that oligodendrocytes, the myelin-maintaining cells of the CNS, lose the capacity to preserve a proper myelin structure and potentially function in age and certain diseases. Here, we made use of directly converted oligodendrocytes (dchiOL) from young, adult and old human donors to study age-associated changes. dchiOL from all three age groups differentiated in an comparable manner into O4 + immature oligodendrocytes, but the proportion of MBP + mature dchiOL decreased with increasing donor age. This was associated with an increased ROS production and upregulation of cellular senescence markers such as CDKN1A, CDKN2A in old dchiOL. Comparison of the transcriptomic profiles of dchiOL from adult and old donors revealed 1324 differentially regulated genes with limited overlap with transcriptomic profiles of the donors' fibroblasts or published data sets from directly converted human neurons or primary rodent oligodendroglial lineage cells. Methylome analyses of dchiOL and human white matter tissue samples demonstrate that chronological and epigenetic age correlate in CNS white matter as well as in dchiOL and resulted in the identification of an age-specific epigenetic signature. Furthermore, we observed an accelerated epigenetic aging of the myelinated, normal appearing white matter of multiple sclerosis (MS) patients compared to healthy individuals. Impaired differentiation and upregulation of cellular senescence markers could be induced in young dchiOL in vitro using supernatants from pro-inflammatory microglia. In summary, our data suggest that physiological aging as well as inflammation-induced cellular senescence contribute to oligodendroglial pathology in inflammatory demyelinating diseases such as MS.

White matter hyperintensity, parent artery steno-occlusion, and neurological deterioration in anterior circulation single subcortical infarction patients.

BACKGROUND: The evidence for the association between white matter hyperintensity (WMH) severity and neurological deterioration (ND) in patients with single subcortical infarction (SSI) remains unclear and whether the association between them is modified by anterior circulation parent artery steno-occlusion (PAS) is unknown. Herein, we aimed to prospectively investigate the internal relevance. METHODS: In this prospective study, the severity of WMH and PAS were assessed in 288 consecutive patients with anterior circulation SSI arriving at our hospital, a tertiary teaching hospital affiliated with Fudan University, 24 h after onset from January 2017 to December 2018. The multivariable logistic regression model was used to estimate the association between WMH severity and the risk of ND within 7 days after stroke onset as well as the interactive effect between WMH severity and PAS on ND among patients with SSI. RESULTS: PAS modified the association between WMH severity and ND among patients with SSI (pinteraction = .029). After multivariate adjustment, the odds ratios of moderate-severe WMH associated with ND were 1.61 (95% CI, 0.50-5.19; ptrend = .428) for patients with PAS, and 0.37 (95% CI, 0.14-0.97; ptrend = .043) for those without PAS. Adding WMH severity to conventional risk factors improved risk prediction for ND in patients without PAS (net reclassification improvement: 48.2%, p = .005; integrated discrimination index: 2.5%, p = .004) but not in those with PAS. CONCLUSION: There was a modified effect of PAS on the association between WMH severity and ND within 7 days after stroke onset among patients with anterior circulation SSI, which deserves more research attention. WMH was negatively associated with ND in anterior circulation SSI patients without PAS.

Deep learning with diffusion MRI as in vivo microscope reveals sex-related differences in human white matter microstructure.

Biological sex is a crucial variable in neuroscience studies where sex differences have been documented across cognitive functions and neuropsychiatric disorders. While gross statistical differences have been previously documented in macroscopic brain structure such as cortical thickness or region size, less is understood about sex-related cellular-level microstructural differences which could provide insight into brain health and disease. Studying these microstructural differences between men and women paves the way for understanding brain disorders and diseases that manifest differently in different sexes. Diffusion MRI is an important in vivo, non-invasive methodology that provides a window into brain tissue microstructure. Our study develops multiple end-to-end classification models that accurately estimates the sex of a subject using volumetric diffusion MRI data and uses these models to identify white matter regions that differ the most between men and women. 471 male and 560 female healthy subjects (age range, 22-37 years) from the Human Connectome Project are included. Fractional anisotropy, mean diffusivity and mean kurtosis are used to capture brain tissue microstructure characteristics. Diffusion parametric maps are registered to a standard template to reduce bias that can arise from macroscopic anatomical differences like brain size and contour. This study employ three major model architectures: 2D convolutional neural networks, 3D convolutional neural networks and Vision Transformer (with self-supervised pretraining). Our results show that all 3 models achieve high sex classification performance (test AUC 0.92-0.98) across all diffusion metrics indicating definitive differences in white matter tissue microstructure between males and females. We further use complementary model architectures to inform about the pattern of detected microstructural differences and the influence of short-range versus long-range interactions. Occlusion analysis together with Wilcoxon signed-rank test is used to determine which white matter regions contribute most to sex classification. The results indicate that sex-related differences manifest in both local features as well as global features / longer-distance interactions of tissue microstructure. Our highly consistent findings across models provides new insight supporting differences between male and female brain cellular-level tissue organization particularly in the central white matter.

White matter integrity of right frontostriatal circuit predicts internet addiction severity among internet gamers.

Excessive use of the internet, which is a typical scenario of self-control failure, could lead to potential consequences such as anxiety, depression, and diminished academic performance. However, the underlying neuropsychological mechanisms remain poorly understood. This study aims to investigate the structural basis of self-control and internet addiction. In a cohort of 96 internet gamers, we examined the relationships among grey matter volume and white matter integrity within the frontostriatal circuits and internet addiction severity, as well as self-control measures. The results showed a significant and negative correlation between dACC grey matter volume and internet addiction severity (p < 0.001), but not with self-control. Subsequent tractography from the dACC to the bilateral ventral striatum (VS) was conducted. The fractional anisotropy (FA) and radial diffusivity of dACC-right VS pathway was negatively (p = 0.011) and positively (p = 0.020) correlated with internet addiction severity, respectively, and the FA was also positively correlated with self-control (p = 0.036). These associations were not observed for the dACC-left VS pathway. Further mediation analysis demonstrated a significant complete mediation effect of self-control on the relationship between FA of the dACC-right VS pathway and internet addiction severity. Our findings suggest that the dACC-right VS pathway is a critical neural substrate for both internet addiction and self-control. Deficits in this pathway may lead to impaired self-regulation over internet usage, exacerbating the severity of internet addiction.

Reversibility of Cognitive Deficits and Functional Connectivity With Transfusion in Children With Sickle Cell Disease.

BACKGROUND AND OBJECTIVES: People with sickle cell disease (SCD) are at risk of cognitive dysfunction independent of stroke. Diminished functional connectivity in select large-scale networks and white matter integrity reflect the neurologic consequences of SCD. Because chronic transfusion therapy is neuroprotective in preventing stroke and strengthening executive function abilities in people with SCD, we hypothesized that red blood cell (RBC) transfusion facilitates the acute reversal of disruptions in functional connectivity while white matter integrity remains unaffected. METHODS: Children with SCD receiving chronic transfusion therapy underwent a brain MRI measuring white matter integrity with diffusion tensor imaging and resting-state functional connectivity within 3 days before and after transfusion of RBCs. Cognitive assessments with the NIH Toolbox were acquired after transfusion and then immediately before the following transfusion cycle. RESULTS: Sixteen children with a median age of 12.5 years were included. Global assessments of functional connectivity using homotopy (p = 0.234) or modularity (p = 0.796) did not differ with transfusion. Functional connectivity within the frontoparietal network significantly strengthened after transfusion (median intranetwork Z-score 0.21 [0.17-0.30] before transfusion, 0.29 [0.20-0.36] after transfusion, p < 0.001), while there was not a significant change seen within the sensory motor, visual, auditory, default mode, dorsal attention, or cingulo-opercular networks. Corresponding to the change within the frontoparietal network, there was a significant improvement in executive function abilities after transfusion (median executive function composite score 87.7 [81.3-90.7] before transfusion, 90.3 [84.3-93.7] after transfusion, p = 0.021). Participants with stronger connectivity in the frontoparietal network before transfusion had a significantly greater improvement in the executive function composite score with transfusion (r = 0.565, 95% CI 0.020-0.851, p = 0.044). While functional connectivity and executive abilities strengthened with transfusion, there was not a significant change in white matter integrity as assessed by fractional anisotropy and mean diffusivity within 16 white matter tracts or globally with tract-based spatial statistics. DISCUSSION: Strengthening of functional connectivity with concomitant improvement in executive function abilities with transfusion suggests that functional connectivity MRI could be used as a biomarker for acutely reversible neurocognitive injury as novel therapeutics are developed for people with SCD.

The association of blood biomarkers with cerebral white matter and myelin content in bipolar disorder: a systematic review.

OBJECTIVES: Evidence from diffusion tensor imaging (DTI) and postmortem studies has demonstrated white-matter (WM) deficits in bipolar disorder (BD). Changes in peripheral blood biomarkers have also been observed; however, studies evaluating the potential relationship between brain alterations and the periphery are scarce. The objective of this systematic review is to investigate the relationship between blood-based biomarkers and WM in BD. METHODS: PubMed, Embase, and PsycINFO were used to conduct literature searches. Cross-sectional or longitudinal studies reporting original data which investigated both a blood-based biomarker and WM (by neuroimaging) in BD were included. RESULTS: Of 3,750 studies retrieved, 23 were included. Several classes of biomarkers were found to have a significant relationship with WM in BD. These included cytokines and growth factors (interleukin-8 [IL-8], tumor necrosis factor alpha [TNF-a], and insulin-like growth factor binding protein 3 [IGFBP-3]), innate immune system (natural killer cells [NK]), metabolic markers (lipid hydroperoxidase, cholesterol, triglycerides), the kynurenine (Kyn) pathway (5-hydroxyindoleacetic acid, kynurenic acid [Kyna]), and various gene polymorphisms (serotonin-transporter-linked promoter region). CONCLUSION: This systematic review revealed that blood-based biomarkers are associated with markers of WM deficits observed in BD. Longitudinal studies investigating the potential clinical utility of these specific biomarkers are encouraged.

Diabetes-related clinical and microstructural white matter changes in patients with Alzheimer's disease.

AIM: Although there exists substantial epidemiological evidence indicating an elevated risk of dementia in individuals with diabetes, our understanding of the neuropathological underpinnings of the association between Type-2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) remains unclear. This study aims to unveil the microstructural brain changes associated with T2DM in AD and identify the clinical variables contributing to these changes. METHODS: In this retrospective study involving 64 patients with AD, 31 individuals had concurrent T2DM. The study involved a comparative analysis of diffusion tensor imaging (DTI) images and clinical features between patients with and without T2DM. The FSL FMRIB software library was used for comprehensive preprocessing and tractography analysis of DTI data. After eddy current correction, the "bedpost" model was utilized to model diffusion parameters. Linear regression analysis with a stepwise method was used to predict the clinical variables that could lead to microstructural white matter changes. RESULTS: We observed a significant impairment in the left superior longitudinal fasciculus (SLF) among patients with AD who also had T2DM. This impairment in patients with AD and T2DM was associated with an elevation in creatine levels. CONCLUSION: The white matter microstructure in the left SLF appears to be sensitive to the impairment of kidney function associated with T2DM in patients with AD. The emergence of AD in association with T2DM may be driven by mechanisms distinct from the typical AD pathology. Compromised renal function in AD could potentially contribute to impaired white matter integrity.

Choir singing is associated with enhanced structural connectivity across the adult lifespan.

The global ageing of populations calls for effective, ecologically valid methods to support brain health across adult life. Previous evidence suggests that music can promote white matter (WM) microstructure and grey matter (GM) volume while supporting auditory and cognitive functioning and emotional well-being as well as counteracting age-related cognitive decline. Adding a social component to music training, choir singing is a popular leisure activity among older adults, but a systematic account of its potential to support healthy brain structure, especially with regard to ageing, is currently missing. The present study used quantitative anisotropy (QA)-based diffusion MRI connectometry and voxel-based morphometry to explore the relationship of lifetime choir singing experience and brain structure at the whole-brain level. Cross-sectional multiple regression analyses were carried out in a large, balanced sample (N = 95; age range 21-88) of healthy adults with varying levels of choir singing experience across the whole age range and within subgroups defined by age (young, middle-aged, and older adults). Independent of age, choir singing experience was associated with extensive increases in WM QA in commissural, association, and projection tracts across the brain. Corroborating previous work, these overlapped with language and limbic networks. Enhanced corpus callosum microstructure was associated with choir singing experience across all subgroups. In addition, choir singing experience was selectively associated with enhanced QA in the fornix in older participants. No associations between GM volume and choir singing were found. The present study offers the first systematic account of amateur-level choir singing on brain structure. While no evidence for counteracting GM atrophy was found, the present evidence of enhanced structural connectivity coheres well with age-typical structural changes. Corroborating previous behavioural studies, the present results suggest that regular choir singing holds great promise for supporting brain health across the adult life span.

Artificial intelligence for volumetric measurement of cerebral white matter hyperintensities on thick-slice fluid-attenuated inversion recovery (FLAIR) magnetic resonance images from multiple centers.

We aimed to develop a new artificial intelligence software that can automatically extract and measure the volume of white matter hyperintensities (WMHs) in head magnetic resonance imaging (MRI) using only thick-slice fluid-attenuated inversion recovery (FLAIR) sequences from multiple centers. We enrolled 1092 participants in Japan, comprising the thick-slice Private Dataset. Based on 207 randomly selected participants, neuroradiologists annotated WMHs using predefined guidelines. The annotated images of participants were divided into training (n = 138) and test (n = 69) datasets. The WMH segmentation model comprised a U-Net ensemble and was trained using the Private Dataset. Two other models were trained for validation using either both thin- and thick-slice MRI datasets or the thin-slice dataset alone. The voxel-wise Dice similarity coefficient (DSC) was used as the evaluation metric. The model trained using only thick-slice MRI showed a DSC of 0.820 for the test dataset, which is comparable to the accuracy of human readers. The model trained with the additional thin-slice dataset showed only a slightly improved DSC of 0.822. This automatic WMH segmentation model comprising a U-Net ensemble trained on a thick-slice FLAIR MRI dataset is a promising new method. Despite some limitations, this model may be applicable in clinical practice.

The impact of sunlight exposure on brain structural markers in the UK Biobank.

Sunlight is closely intertwined with daily life. It remains unclear whether there are associations between sunlight exposure and brain structural markers. General linear regression analysis was used to compare the differences in brain structural markers among different sunlight exposure time groups. Stratification analyses were performed based on sex, age, and diseases (hypertension, stroke, diabetes). Restricted cubic spline was performed to examine the dose-response relationship between natural sunlight exposure and brain structural markers, with further stratification by season. A negative association of sunlight exposure time with brain structural markers was found in the upper tertile compared to the lower tertile. Prolonged natural sunlight exposure was associated with the volumes of total brain (ß: - 0.051, P < 0.001), white matter (ß: - 0.031, P = 0.023), gray matter (ß: - 0.067, P < 0.001), and white matter hyperintensities (ß: 0.059, P < 0.001). These associations were more pronounced in males and individuals under the age of 60. The results of the restricted cubic spline analysis showed a nonlinear relationship between sunlight exposure and brain structural markers, with the direction changing around 2 h of sunlight exposure. This study demonstrates that prolonged exposure to natural sunlight is associated with brain structural markers change.

Multi-level prediction of substance use: Interaction of white matter integrity, resting-state connectivity and inhibitory control measured repeatedly in every-day life.

Substance use disorders are characterized by inhibition deficits related to disrupted connectivity in white matter pathways, leading via interaction to difficulties in resisting substance use. By combining neuroimaging with smartphone-based ecological momentary assessment (EMA), we questioned how biomarkers moderate inhibition deficits to predict use. Thus, we aimed to assess white matter integrity interaction with everyday inhibition deficits and related resting-state network connectivity to identify multi-dimensional predictors of substance use. Thirty-eight patients treated for alcohol, cannabis or tobacco use disorder completed 1 week of EMA to report substance use five times and complete Stroop inhibition testing twice daily. Before EMA tracking, participants underwent resting state functional MRI and diffusion tensor imaging (DTI) scanning. Regression analyses were conducted between mean Stroop performances and whole-brain fractional anisotropy (FA) in white matter. Moderation testing was conducted between mean FA within significant clusters as moderator and the link between momentary Stroop performance and use as outcome. Predictions between FA and resting-state connectivity strength in known inhibition-related networks were assessed using mixed modelling. Higher FA values in the anterior corpus callosum and bilateral anterior corona radiata predicted higher mean Stroop performance during the EMA week and stronger functional connectivity in occipital-frontal-cerebellar regions. Integrity in these regions moderated the link between inhibitory control and substance use, whereby stronger inhibition was predictive of the lowest probability of use for the highest FA values. In conclusion, compromised white matter structural integrity in anterior brain systems appears to underlie impairment in inhibitory control functional networks and compromised ability to refrain from substance use.

Human intraparietal sulcal morphology relates to individual differences in language and memory performance.

The sulco-gyral pattern is a qualitative feature of the cortical anatomy that is determined in utero, stable throughout lifespan and linked to brain function. The intraparietal sulcus (IPS) is a nodal associative brain area, but the relation between its morphology and cognition is largely unknown. By labelling the left and right IPS of 390 healthy participants into two patterns, according to the presence or absence of a sulcus interruption, here we demonstrate a strong association between the morphology of the right IPS and performance on memory and language tasks. We interpret the results as a morphological advantage of a sulcus interruption, probably due to the underlying white matter organization. The right-hemisphere specificity of this effect emphasizes the neurodevelopmental and plastic role of sulcus morphology in cognition prior to lateralisation processes. The results highlight a promising area of investigation on the relationship between cognitive performance, sulco-gyral pattern and white matter bundles.

Predicting Alzheimer's progression in MCI: a DTI-based white matter network model.

OBJECTIVE: This study aimed to identify features of white matter network attributes based on diffusion tensor imaging (DTI) that might lead to progression from mild cognitive impairment (MCI) and construct a comprehensive model based on these features for predicting the population at high risk of progression to Alzheimer's disease (AD) in MCI patients. METHODS: This study enrolled 121 MCI patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Among them, 36 progressed to AD after four years of follow-up. A brain network was constructed for each patient based on white matter fiber tracts, and network attribute features were extracted. White matter network features were downscaled, and white matter markers were constructed using an integrated downscaling approach, followed by forming an integrated model with clinical features and performance evaluation. RESULTS: APOE4 and ADAS scores were used as independent predictors and combined with white matter network markers to construct a comprehensive model. The diagnostic efficacy of the comprehensive model was 0.924 and 0.919, sensitivity was 0.864 and 0.900, and specificity was 0.871 and 0.815 in the training and test groups, respectively. The Delong test showed significant differences (P < 0.05) in the diagnostic efficacy of the combined model and APOE4 and ADAS scores, while there was no significant difference (P > 0.05) between the combined model and white matter network biomarkers. CONCLUSIONS: A comprehensive model constructed based on white matter network markers can identify MCI patients at high risk of progression to AD and provide an adjunct biomarker helpful in early AD detection.

Decreased brain iron deposition based on quantitative susceptibility mapping correlates with reduced neurodevelopmental status in children with autism spectrum disorder.

To investigate potential correlations between the susceptibility values of certain brain regions and the severity of disease or neurodevelopmental status in children with autism spectrum disorder (ASD), 18 ASD children and 15 healthy controls (HCs) were recruited. The neurodevelopmental status was assessed by the Gesell Developmental Schedules (GDS) and the severity of the disease was evaluated by the Autism Behavior Checklist (ABC). Eleven brain regions were selected as regions of interest and the susceptibility values were measured by quantitative susceptibility mapping. To evaluate the diagnostic capacity of susceptibility values in distinguishing ASD and HC, the receiver operating characteristic (ROC) curve was computed. Pearson and Spearman partial correlation analysis were used to depict the correlations between the susceptibility values, the ABC scores, and the GDS scores in the ASD group. ROC curves showed that the susceptibility values of the left and right frontal white matter had a larger area under the curve in the ASD group. The susceptibility value of the right globus pallidus was positively correlated with the GDS-fine motor scale score. These findings indicated that the susceptibility value of the right globus pallidus might be a viable imaging biomarker for evaluating the neurodevelopmental status of ASD children.

Modulation of the Association Between Corticospinal Tract Damage and Outcome After Stroke by White Matter Hyperintensities.

BACKGROUND AND OBJECTIVES: Motor outcomes after stroke relate to corticospinal tract (CST) damage. The brain leverages surviving neural pathways to compensate for CST damage and mediate motor recovery. Thus, concurrent age-related damage from white matter hyperintensities (WMHs) might affect neurologic capacity for recovery after CST injury. The role of WMHs in post-stroke motor outcomes is unclear. In this study, we evaluated whether WMHs modulate the relationship between CST damage and post-stroke motor outcomes. METHODS: We used data from the multisite ENIGMA Stroke Recovery Working Group with T1 and T2/fluid-attenuated inversion recovery imaging. CST damage was indexed with weighted CST lesion load (CST-LL). WMH volumes were extracted with Freesurfer's SAMSEG. Mixed-effects beta-regression models were fit to test the impact of CST-LL, WMH volume, and their interaction on motor impairment, controlling for age, days after stroke, and stroke volume. RESULTS: A total of 223 individuals were included. WMH volume related to motor impairment above and beyond CST-LL (ß = 0.178, 95% CI 0.025-0.331, p = 0.022). Relationships varied by WMH severity (mild vs moderate-severe). In individuals with mild WMHs, motor impairment related to CST-LL (ß = 0.888, 95% CI 0.604-1.172, p < 0.001) with a CST-LL × WMH interaction (ß = -0.211, 95% CI -0.340 to -0.026, p = 0.026). In individuals with moderate-severe WMHs, motor impairment related to WMH volume (ß = 0.299, 95% CI 0.008-0.590, p = 0.044), but did not significantly relate to CST-LL or a CST-LL × WMH interaction. DISCUSSION: WMHs relate to motor outcomes after stroke and modify relationships between motor impairment and CST damage. WMH-related damage may be under-recognized in stroke research as a factor contributing to variability in motor outcomes. Our findings emphasize the importance of brain structural reserve in motor outcomes after brain injury.