Sex disparity of cerebral white matter hyperintensity in the hypertensive elderly: The Shanghai Changfeng study.

White matter hyperintensity (WMH) is associated with vascular hemodynamic alterations and reflects white matter injury. To date, the sex difference of tract-specific WMH and the relationship between high blood pressure (BP) and tract-specific WMH remain unclear. We recruited 515 subjects from the Shanghai Changfeng study (range 53-89 years, mean age 67.33 years). Systolic and diastolic blood pressure (SBP and DBP) were collected and used to calculate pulse pressure (PP). Magnetic resonance T1 and T2 FLAIR images were acquired to measure WMH and calculate WMH index. The ANCOVA test was performed to test the difference between sexes, and the linear regression model was used to examine the associations between BP and WMH index. Men showed higher WMH index than women in all white matter tracts (p < .001, respectively) except for the bilateral superior longitudinal fasciculus (SLF) and its left temporal part (tSLF). High SBP and PP was associated with a lower WMH index on the left corticospinal tract (CST), SLF, tSLF and right cingulum in hippocampus (p ≤ .001, respectively) in women, while high DBP was associated with a higher WMH index on the bilateral CST (left p < .001; right p = .001), left inferior longitudinal fasciculus (p < .001) and inferior fronto-occipital fasciculus (p = .002) in men. Men tend to have more WMH compared to women. A high SBP/PP relates to a lower WMH burden in women. This suggests that women could benefit from higher blood pressure in older age.

The Human Brain Is Best Described as Being on a Female/Male Continuum: Evidence from a Neuroimaging Connectivity Study.

Psychological androgyny has long been associated with greater cognitive flexibility, adaptive behavior, and better mental health, but whether a similar concept can be defined using neural features remains unknown. Using the neuroimaging data from 9620 participants, we found that global functional connectivity was stronger in the male brain before middle age but became weaker after that, when compared with the female brain, after systematic testing of potentially confounding effects. We defined a brain gender continuum by estimating the likelihood of an observed functional connectivity matrix to represent a male brain. We found that participants mapped at the center of this continuum had fewer internalizing symptoms compared with those at the 2 extreme ends. These findings suggest a novel hypothesis proposing that there exists a neuroimaging concept of androgyny using the brain gender continuum, which may be associated with better mental health in a similar way to psychological androgyny.

Differential associations of visual memory with hippocampal subfields in subjective cognitive decline and amnestic mild cognitive impairment.

BACKGROUND: Although previous studies have demonstrated that the hippocampus plays a role in verbal memory, the role of hippocampal subfields in visual memory is uncertain, especially in those with preclinical Alzheimer's disease (AD). This study aimed to examine relationships between hippocampal subfield volumes and visual memory in SCD (subjective cognitive decline) and aMCI (amnestic mild cognitive impairment). METHODS: The study sample included 47 SCD patients, 62 aMCI patients, and 51 normal controls (NCs) and was recruited from Shanghai Jiao Tong University Affiliated Sixth People's Hospital. Visual memory was measured by the subtests of BVMT-R (Brief Visuospatial Memory Test-Revised), PLT (Pictorial Learning Test), DMS (Delayed Matching to Sample), and PAL (Paired Associates Learning). Hippocampal subfield volumes were estimated using FreeSurfer software (version 6.0). We modeled the association between visual memory and relative hippocampal subfield volumes (dividing by estimated total intracranial volume) using Pearson's correlation and linear regression. RESULTS: Compared with the NC group, patients with SCD did not find any relative hippocampal subregion atrophy, and the aMCI group found atrophy in CA1, molecular layer, subiculum, GC-ML-DG, CA4, and CA3. After adjusting for covariates (age, sex, and APOE ε4 status) and FDR (false discovery rate) correction of p (q values) < 0.05, in NC group, DMS delay matching scores were significant and negatively associated with presubiculum (r = -0.399, FDR q = 0.024); in SCD group, DMS delay matching scores were negatively associated with CA3 (r = -0.378, FDR q = 0.048); in the aMCI group, BVMT-R immediate recall scores were positively associated with CA1, molecular layer, subiculum, and GC-ML-DG (r = 0.360-0.374, FDR q < 0.036). Stepwise linear regression analysis confirmed the association. CONCLUSIONS: Our results indicate a different and specific correction of visual memory with relative hippocampal subfield volumes between SCD and aMCI. The correlations involved different and more subfields as cognitive decline. Whether these associations predict future disease progression needs dynamic longitudinal studies.

Sensory, somatomotor and internal mentation networks emerge dynamically in the resting brain with internal mentation predominating in older age.

Age-related changes in the brain are associated with a decline in functional flexibility. Intrinsic functional flexibility is evident in the brain's dynamic ability to switch between alternative spatiotemporal states during resting state. However, the relationship between brain connectivity states, associated psychological functions during resting state, and the changes in normal aging remain poorly understood. In this study, we analyzed resting-state functional magnetic resonance imaging (rsfMRI) data from the Human Connectome Project (HCP; N = 812) and the UK Biobank (UKB; N = 6,716). Using signed community clustering to identify distinct states of dynamic functional connectivity, and text-mining of a large existing literature for functional annotation of each state, our findings from the HCP dataset indicated that the resting brain spontaneously transitions between three functionally specialized states: sensory, somatomotor, and internal mentation networks. The occurrence, transition-rate, and persistence-time parameters for each state were correlated with behavioural scores using canonical correlation analysis. We estimated the same brain states and parameters in the UKB dataset, subdivided into three distinct age ranges: 50-55, 56-67, and 68-78 years. We found that the internal mentation network was more frequently expressed in people aged 71 and older, whereas people younger than 55 more frequently expressed sensory and somatomotor networks. Furthermore, analysis of the functional entropy - a measure of uncertainty of functional connectivity - also supported this finding across the three age ranges. Our study demonstrates that dynamic functional connectivity analysis can expose the time-varying patterns of transition between functionally specialized brain states, which are strongly tied to increasing age.

Beyond the disconnectivity hypothesis of schizophrenia.

To go beyond the disconnectivity hypothesis of schizophrenia, directed (effective) connectivity was measured between 94 brain regions, to provide evidence on the source of the changes in schizophrenia and a mechanistic model. Effective connectivity (EC) was measured in 180 participants with schizophrenia and 208 controls. For the significantly different effective connectivities in schizophrenia, on average the forward (stronger) effective connectivities were smaller, whereas the backward connectivities tended to be larger. Further, higher EC in schizophrenia was found from the precuneus and posterior cingulate cortex (PCC) to areas such as the parahippocampal, hippocampal, temporal, fusiform, and occipital cortices. These are backward effective connectivities and were positively correlated with the positive symptoms of schizophrenia. Lower effective connectivities were found from temporal and other regions and were negatively correlated with the symptoms, especially the negative and general symptoms. Further, a signal variance parameter was increased for areas that included the parahippocampal gyrus and hippocampus, consistent with the hypothesis that hippocampal overactivity is involved in schizophrenia. This investigation goes beyond the disconnectivity hypothesis by drawing attention to differences in schizophrenia between backprojections and forward connections, with the backward connections from the precuneus and PCC implicated in memory stronger in schizophrenia.

A powerful and efficient multivariate approach for voxel-level connectome-wide association studies.

We describe an approach to multivariate analysis, termed structured kernel principal component regression (sKPCR), to identify associations in voxel-level connectomes using resting-state functional magnetic resonance imaging (rsfMRI) data. This powerful and computationally efficient multivariate method can identify voxel-phenotype associations based on the whole-brain connectivity pattern of voxels, and it can detect linear and non-linear signals in both volume-based and surface-based rsfMRI data. For each voxel, sKPCR first extracts low-dimensional signals from the spatially smoothed connectivities by structured kernel principal component analysis, and then tests the voxel-phenotype associations by an adaptive regression model. The method's power is derived from appropriately modelling the spatial structure of the data when performing dimension reduction, and then adaptively choosing an optimal dimension for association testing using the adaptive regression strategy. Simulations based on real connectome data have shown that sKPCR can accurately control the false-positive rate and that it is more powerful than many state-of-the-art approaches, such as the connectivity-wise generalized linear model (GLM) approach, multivariate distance matrix regression (MDMR), adaptive sum of powered score (aSPU) test, and least-square kernel machine (LSKM). Moreover, since sKPCR can reduce the computational cost of non-parametric permutation tests, its computation speed is much faster. To demonstrate the utility of sKPCR for real data analysis, we have also compared sKPCR with the above methods based on the identification of voxel-wise differences between schizophrenic patients and healthy controls in four independent rsfMRI datasets. The results showed that sKPCR had better between-sites reproducibility and a larger proportion of overlap with existing schizophrenia meta-analysis findings. Code for our approach can be downloaded from https://github.com/weikanggong/sKPCR.

Randomization and resilience of brain functional networks as systems-level endophenotypes of schizophrenia.

Schizophrenia is increasingly conceived as a disorder of brain network organization or dysconnectivity syndrome. Functional MRI (fMRI) networks in schizophrenia have been characterized by abnormally random topology. We tested the hypothesis that network randomization is an endophenotype of schizophrenia and therefore evident also in nonpsychotic relatives of patients. Head movement-corrected, resting-state fMRI data were acquired from 25 patients with schizophrenia, 25 first-degree relatives of patients, and 29 healthy volunteers. Graphs were used to model functional connectivity as a set of edges between regional nodes. We estimated the topological efficiency, clustering, degree distribution, resilience, and connection distance (in millimeters) of each functional network. The schizophrenic group demonstrated significant randomization of global network metrics (reduced clustering, greater efficiency), a shift in the degree distribution to a more homogeneous form (fewer hubs), a shift in the distance distribution (proportionally more long-distance edges), and greater resilience to targeted attack on network hubs. The networks of the relatives also demonstrated abnormal randomization and resilience compared with healthy volunteers, but they were typically less topologically abnormal than the patients' networks and did not have abnormal connection distances. We conclude that schizophrenia is associated with replicable and convergent evidence for functional network randomization, and a similar topological profile was evident also in nonpsychotic relatives, suggesting that this is a systems-level endophenotype or marker of familial risk. We speculate that the greater resilience of brain networks may confer some fitness advantages on nonpsychotic relatives that could explain persistence of this endophenotype in the population.

Functional brain network changes associated with clinical and biochemical measures of the severity of hepatic encephalopathy.

Functional properties of the brain may be associated with changes in complex brain networks. However, little is known about how properties of large-scale functional brain networks may be altered stepwise in patients with disturbance of consciousness, e.g., an encephalopathy. We used resting-state fMRI data on patients suffering from various degrees of hepatic encephalopathy (HE) to explore how topological and spatial network properties of functional brain networks changed at different cognitive and consciousness states. Severity of HE was measured clinically and by neuropsychological tests. Fifty-eight non-alcoholic liver cirrhosis patients and 62 normal controls were studied. Patients were subdivided into liver cirrhosis with no outstanding HE (NoHE, n=23), minimal HE with cognitive impairment only detectable by neuropsychological tests (MHE, n=28), and clinically overt HE (OHE, n=7). From the earliest stage, the NoHE, functional brain networks were progressively more random, less clustered, and less modular. Since the intermediate stage (MHE), increased ammonia level was accompanied by concomitant exponential decay of mean connectivity strength, especially in the primary cortical areas and midline brain structures. Finally, at the OHE stage, there were radical reorganization of the topological centrality-i.e., the relative importance-of the hubs and reorientation of functional connections between nodes. In summary, this study illustrated progressively greater abnormalities in functional brain network organization in patients with clinical and biochemical evidence of more severe hepatic encephalopathy. The early-than-expected brain network dysfunction in cirrhotic patients suggests that brain functional connectivity and network analysis may provide useful and complementary biomarkers for more aggressive and earlier intervention of hepatic encephalopathy. Moreover, the stepwise deterioration of functional brain networks in HE patients may suggest that hierarchical network properties are necessary for normal brain function.

Short-term Medication Effects on Brain Functional Activity and Network Architecture in First-Episode psychosis: a longitudinal fMRI study.

The effect of antipsychotic medications is critical for the long-term outcome of symptoms and functions during first-episode psychosis (FEP). However, how brain functions respond to the antipsychotic treatment in the early stage of psychosis and its underlying neural mechanisms remain unclear. In this study, we explored the cross-sectional and longitudinal changes of regional homogeneity (ReHo), whole-brain functional connectivity, and network topological properties via resting-state functional magnetic resonance images. Thirty-two drug-naïve FEP patients and 30 matched healthy volunteers (HV) were included, where 23 patients were re-visited with effective responses after two months of antipsychotic treatment. Compared to HV, drug-naive patients demonstrated significantly different patterns of functional connectivity involving the right thalamus. These functional alterations mainly involved decreased ReHo, increased nodal efficiency in the right thalamus, and increased thalamic-sensorimotor-frontoparietal connectivity. In the follow-up analysis, patients after treatment showed reduced ReHo and nodal clustering in visual networks, as well as disturbances of visual-somatomotor and hippocampus-superior frontal gyrus connectivity. The longitudinal changes of ReHo in the visual cortex were associated with an improvement in general psychotic symptoms. This study provides new evidence regarding alterations in brain function linked to schizophrenia onset and affected by antipsychotic medications. Moreover, our results demonstrated that the functional alterations at baseline were not fully modulated by antipsychotic medications, suggesting that antipsychotic medications may reduce psychotic symptoms but limit the effects in regions involved in disease pathophysiology.

Structure-function coupling in white matter uncovers the abnormal brain connectivity in Schizophrenia.

Schizophrenia is characterized by dysconnectivity syndrome. Evidence of widespread impairment of structural and functional integration has been demonstrated in schizophrenia. Although white matter (WM) microstructural abnormalities have been commonly reported in schizophrenia, the dysfunction of WM as well as the relationship between structure and function in WM remains uncertain. In this study, we proposed a novel structure-function coupling measurement to reflect neuronal information transfer, which combined spatial-temporal correlations of functional signals with diffusion tensor orientations in the WM circuit from functional and diffusion magnetic resonance images (MRI). By analyzing MRI data from 75 individuals with schizophrenia (SZ) and 89 healthy volunteers (HV), the associations between structure and function in WM regions in schizophrenia were examined. Randomized validation of the measurement was performed in the HV group to confirm the capacity of the neural signal transferring along the WM tracts, referring to quantifying the association between structure and function. Compared to HV, SZ showed a widespread decrease in the structure-function coupling within WM regions, involving the corticospinal tract and the superior longitudinal fasciculus. Additionally, the structure-function coupling in the WM tracts was found to be significantly correlated with psychotic symptoms and illness duration in schizophrenia, suggesting that abnormal signal transfer of neuronal fiber pathways could be a potential mechanism of the neuropathology of schizophrenia. This work supports the dysconnectivity hypothesis of schizophrenia from the aspect of circuit function, and highlights the critical role of WM networks in the pathophysiology of schizophrenia.

Brain amyloid-ß deposition associated functional connectivity changes of ultra-large structural scale in mild cognitive impairment.

In preclinical Alzheimer's disease, neuro-functional changes due to amyloid-ß (Aß) deposition are not synchronized in different brain lobes and subcortical nuclei. This study aimed to explore the correlation between brain Aß burden, connectivity changes in an ultra-large structural scale, and cognitive function in mild cognitive impairment. Participants with mild cognitive impairment were recruited and underwent florbetapir (F18-AV45) PET, resting-state functional MRI, and multidomain neuropsychological tests. AV-45 standardized uptake value ratio (SUVR) and functional connectivity of all participants were calculated. Of the total 144 participants, 72 were put in the low Aß burden group and 72 in the high Aß burden group. In the low Aß burden group, all connectivities between lobes and nuclei had no correlation with SUVR. In the high Aß burden group, SUVR showed negative correlations with the Subcortical-Occipital connectivity (r=-0.36, P = 0.02) and Subcortical-Parietal connectivity (r=-0.26, P = 0.026). Meanwhile, in the high Aß burden group, SUVR showed positive correlations with the Temporal-Prefrontal connectivity (r = 0.27, P = 0.023), Temporal-Occipital connectivity (r = 0.24, P = 0.038), and Temporal-Parietal connectivity (r = 0.32, P = 0.006). Subcortical to Occipital and Parietal connectivities had positive correlations with general cognition, language, memory, and executive function. Temporal to Prefrontal, Occipital, and Parietal connectivities had negative correlations with memory function, executive function, and visuospatial function, and a positive correlation with language function. In conclusion, Individuals with mild cognitive impairment with high Aß burden have Aß-related bidirectional functional connectivity changes between lobes and subcortical nuclei that are associated with cognitive decline in multiple domains. These connectivity changes reflect neurological impairment and failed compensation.

Impaired type I interferon signaling activity implicated in the peripheral blood transcriptome of preclinical Alzheimer's disease.

BACKGROUND: Subjective or objective subtle cognitive decline (SCD) is considered the preclinical manifestation of Alzheimer's disease (AD), which is a potentially crucial window for preventing or delaying the progression of the disease. METHODS: To explore the potential mechanism of disease progression and identify relevant biomarkers, we comprehensively assessed the peripheral blood transcriptomic alterations in SCD, covering lncRNA, mRNA, and miRNA. FINDINGS: Dysregulated protein-coding mRNA at both gene and isoform levels implicated impairment in the type I interferon signaling pathway in SCD. Specifically, this pathway was regulated by the transcription factor STAT1 and ncRNAs NRIR and has-miR-146a-5p. The miRNA-mRNA-lncRNA co-expression network revealed hub genes for the interferon module. Individuals with lower interferon signaling activity and lower expression of a hub gene STAT1 exhibited a higher conversion rate to mild cognitive impairment (MCI). INTERPRETATION: Our findings illustrated the down-regulation of interferon signaling activity would potentially increase the risk of disease progression and thus serve as a pre-disease biomarker. FUNDING: This work was partly supported by National Key R&D Program of China (2020YFA0712403), National Natural Science Foundation of China (61932008), Shanghai Municipal Science and Technology Major Project (2018SHZDZX01), the 111 Project (No. B18015) of China, Greater Bay Area Institute of Precision Medicine (Guangzhou) (Grand No. IPM21C008), Natural Science Foundation of Shanghai (21ZR1403200), and Shanghai Center for Brain Science and Brain-Inspired Technology.

Altered metamemory precedes cognitive impairment in subjective cognitive decline with positive amyloid-beta.

Subjective cognitive decline (SCD) as an indicator of preclinical Alzheimer's disease (AD) may precede mild cognitive impairment (MCI) over several decades. Self-reported cognitive decline as a typical clinical manifestation is critical in preclinical AD. Metacognition represents a person's ability to accurately assess cognition. Our study aimed to examine (1) the alternations of metamemory in a cohort across the Alzheimer's continuum, (2) the association between metamemory and cognition, and (3) the relationship of cortical thickness in four regions of interest (ROI) with metamemory scores. Six hundred ninety-seven participants were classified as 79 AD dementia, 161 aMCI, 261 SCD, and 196 cognitively unimpaired (CU) individuals, in which 418 participants aged above 65, 131 participants with Aß+ after receiving positron emission tomography, and 602 participants received sMRI. The degree of confidence (DOC) was measured by calculating discrepancies between judgments and memory performance. We assessed the relationships between DOC tertiles and cognition and analyzed the screening power, then investigated the partial correlation between DOC and ROIs, controlled by age, sex, and cognition. In the Aß+ subgroup, SCD showed significantly higher DOC scores than the CU group. There was an increasing trend of overconfidence with the decline of cognition across the AD spectrum (P for trend < 0.001). After adjusting for age, sex, and education, the lower degree of confidence-long-term delay recall (DOC-LD) tertiles were associated with lower odds ratio in SCD, aMCI, and AD in the Aß+ subgroup (all P for trend < 0.05). The area under the curves of DOC scores for screening SCD from CU in the Aß+ subgroup was better than that in all participants and the age ≥65 subgroup. Partial correlation showed that in the Aß+ subgroup, DOC-SD (degree of confidence-short-term delay recall) was negatively correlated with the anterior cingulate cortex; DOC-LD was negatively correlated with the cortices of parahippocampal, anterior cingulate, posterior cingulate, and medial orbitofrontal. In individuals with Aß+, SCD exhibited a detectable metamemory alternation before objective cognitive impairment could be tested, indicated by the overestimation in the memory performance. The pattern of an increasing trend of overconfidence across SCD, aMCI, and AD dementia supports the view of a continuum in Alzheimer's disease.

Graph theoretical analysis of human brain structural networks.

There is a growing interest in exploring the connectivity patterns of the human brain. Specifically, the utility of noninvasive neuroimaging data and graph theoretical analysis have provided important insights into the anatomical connections and topological pattern of human brain structural networks in vivo. This review focuses on recent methodological and application studies, utilizing graph theoretical approaches, on brain structural networks with structural magnetic resonance imaging (MRI) and diffusion MRI. These studies showed many nonrandom properties of structural brain networks, such as small-worldness, modularity, and highly connected hubs. Importantly, topological organization of the networks shows changes during normal development, aging, and neuropsychiatric diseases. Network structures have also been found to correlate with behavioral or cognitive functions, which imply their associations with functional dynamics. These advances not only help us to understand how the healthy human brain is structurally organized, but also provide a novel insight into the biological mechanisms of brain disorders. Future studies will involve the combination of structural/diffusion MRI and functional MRI, to realize how the structural connectivity patterns of the brain underlie its functional states, and will explore whether graph theoretical analysis of structural brain networks could serve as potential imaging biomarkers for disease diagnosis and treatment.

Differential Patterns of Gyral and Sulcal Morphological Changes During Normal Aging Process.

The cerebral cortex is a highly convoluted structure with distinct morphologic features, namely the gyri and sulci, which are associated with the functional segregation or integration in the human brain. During the lifespan, the brain atrophy that is accompanied by cognitive decline is a well-accepted aging phenotype. However, the detailed patterns of cortical folding change during aging, especially the changing age-dependencies of gyri and sulci, which is essential to brain functioning, remain unclear. In this study, we investigated the morphology of the gyral and sulcal regions from pial and white matter surfaces using MR imaging data of 417 healthy participants across adulthood to old age (21-92 years). To elucidate the age-related changes in the cortical pattern, we fitted cortical thickness and intrinsic curvature of gyri and sulci using the quadratic model to evaluate their age-dependencies during normal aging. Our findings show that comparing to gyri, the sulcal thinning is the most prominent pattern during the aging process, and the gyrification of pial and white matter surfaces were also affected differently, which implies the vulnerability of functional segregation during aging. Taken together, we propose a morphological model of aging that may provide a framework for understanding the mechanisms underlying gray matter degeneration.

Connectivity-Based Topographical Changes of the Corpus Callosum During Aging.

Background: The corpus callosum (CC) is the most prominent white matter connection for interhemispheric information transfer. It is implicated in a variety of cognitive functions, which tend to decline with age. The region-specific projections of the fiber bundles with microstructural heterogeneity of the CC are associated with cognitive functions and diseases. However, how the CC is associated with the information transfer within functional networks and the connectivity changes during aging remain unclear. Studying the CC topography helps to understand the functional specialization and age-related changes of CC subregions. Methods: Diffusion tractography was used to subdivide the CC into seven subregions from 1,086 healthy volunteers within a wide age range (21-90 years), based on the connections to the cortical parcellations of the functional networks. Quantitative diffusion indices and connection probability were calculated to study the microstructure differences and age-related changes in the CC subregions. Results: According to the population-based probabilistic topography of the CC, part of the default mode network (DMN) and limbic network (LN) projected fibers through the genu and rostrum; the frontoparietal network (FPN), ventral attention network (VA) and somatomotor networks (SM) were interconnected by the CC body; callosal fibers arising from the part of the default mode network (DMN), dorsal attention network (DA) and visual network (VIS) passed through the splenium. Anterior CC subregions interconnecting DMN, LN, FPN, VA, and SM showed lower fractional anisotropy (FA) and higher mean diffusivity (MD) and radial diffusivity (RD) than posterior CC subregions interconnecting DA and VIS. All the CC subregions showed slightly increasing FA and decreasing MD, RD, and axial diffusivity (AD) at younger ages and opposite trends at older ages. Besides, the anterior CC subregions exhibited larger microstructural and connectivity changes compared with the posterior CC subregions during aging. Conclusion: This study revealed the callosal subregions related to functional networks and uncovered an overall "anterior-to-posterior" region-specific changing trend during aging, which provides a baseline to identify the presence and timing of callosal connection states.

Differential Age Trajectories of White Matter Changes Between Sexes Correlate with Cognitive Performances.

Background: Aging is accompanied by a gradual deterioration in multiple cognitive abilities and brain structures. Both cognitive function and white matter (WM) structure are found to be associated with neurodegeneration diseases and correlated with sex during aging. However, it is still unclear whether the brain structural change could be attributable to sex, and how sex would affect cognitive performances during aging. Materials and Methods: Diffusion magnetic resonance imaging (MRI) scans were performed on 1127 healthy participants (age range: 21-89) at a single site. The age trajectories of the WM tract microstructure were delineated to estimate the turning age and changing rate between sexes. The canonical correlation analysis and moderated mediation analysis were used to examine the relationship between sex-linked WM tracts and cognitive performances. Results: The axon intactness and demyelination of sex-linked tracts during aging were multifaceted. Sex-linked tracts in females peak around 5 years later than those in males but change significantly faster after the turning age. Projection and association tracts (e.g., corticospinal tracts and parahippocampal cingulum) contributed to a significant decrease in visuospatial functions (VS) and executive functions (E). We discovered that there is a stronger indirect effect of sex-linked tracts on cognitive functions in females than in males. Conclusion: Our findings suggest that the vulnerable projection and association tracts in females may induce negative impacts on integrating multiple functions, which results in a faster decrease in VS and E. Impact statement By recruiting a healthy population for diffusion magnetic resonance imaging (MRI) scan, we demonstrated that the age-related changes of white matter (WM) integrity were manipulated by sex. Sex-linked tracts in females reached the turning age 5 years later, but change faster than those in males after the turning age. The most significant sex effect was found in projection and association tracts. Our results indicated that sex affected both WM microstructure and cognitive functions and was further involved in the mediation of the age-WM-cognition relationship. The vulnerability of projection and association tracts in females may induce negative impacts on visuospatial and executive functions.

Neural Biomarkers Distinguish Severe From Mild Autism Spectrum Disorder Among High-Functioning Individuals.

Several previous studies have reported atypicality in resting-state functional connectivity (FC) in autism spectrum disorder (ASD), yet the relatively small effect sizes prevent us from using these characteristics for diagnostic purposes. Here, canonical correlation analysis (CCA) and hierarchical clustering were used to partition the high-functioning ASD group (i.e., the ASD discovery group) into subgroups. A support vector machine (SVM) model was trained through the 10-fold strategy to predict Autism Diagnostic Observation Schedule (ADOS) scores within the ASD discovery group (r = 0.30, P < 0.001, n = 260), which was further validated in an independent sample (i.e., the ASD validation group) (r = 0.35, P = 0.031, n = 29). The neuroimage-based partition derived two subgroups representing severe versus mild autistic patients. We identified FCs that show graded changes in strength from ASD-severe, through ASD-mild, to controls, while the same pattern cannot be observed in partitions based on ADOS score. We also identified FCs that are specific for ASD-mild, similar to a partition based on ADOS score. The current study provided multiple pieces of evidence with replication to show that resting-state functional magnetic resonance imaging (rsfMRI) FCs could serve as neural biomarkers in partitioning high-functioning autistic individuals based on their symptom severity and showing advantages over traditional partition based on ADOS score. Our results also indicate a compensatory role for a frontocortical network in patients with mild ASD, indicating potential targets for future clinical treatments.

Incidental Brain Magnetic Resonance Imaging Findings and the Cognitive and Motor Performance in the Elderly: The Shanghai Changfeng Study.

BACKGROUND: The frequently discovered incidental findings (IFs) from imaging observations are increasing. The IFs show the potential clues of structural abnormalities underlying cognitive decline in elders. Detecting brain IFs and their relationship with cognitive and behavioral functions helps provide the information for clinical strategies. METHODS: Five hundred and seventy-nine participants were recruited in the Shanghai Changfeng Study. All participants performed the demographic, biochemical, and cognitive functions and gait speed assessment and underwent the high-resolution multimodal magnetic resonance imaging scans. We calculated the detection rate of brain IFs. The association between cardiovascular risk factors and IFs and the associations between IFs and cognitive and motor functions were assessed using regression models. The relationships among gray matter volume, cognitive function, and gait speed were assessed with/without adjusting the IFs to evaluate the effects of potential IFs confounders. RESULTS: IFs were found in a total of 578 subjects with a detection rate of 99.8%. Age and blood pressure were the most significant cardiovascular risk factors correlated with IFs. IFs were found to be negatively associated with Montreal Cognitive Assessment, Mini-Mental State Examination, and gait speed. The gray matter volume was found to be positively correlated with the cognitive function without adjusting the white matter hyperintensity but not if adjusted. CONCLUSION: IFs are commonly found in the elderly population and related to brain functions. The adequate intervention of IFs related cardiovascular risk factors that may slow down the progression of brain function decline. We also suggest that IFs should be considered as confounding factors that may affect cognitive issues on the structural neuroimaging researches in aging or diseases.

The role of brain perivascular space burden in early-stage Parkinson's disease.

Perivascular space (PVS) is associated with neurodegenerative diseases, while its effect on Parkinson's disease (PD) remains unclear. We aimed to investigate the clinical and neuroimaging significance of PVS in basal ganglia (BG) and midbrain in early-stage PD. We recruited 40 early-stage PD patients and 41 healthy controls (HCs). Both PVS number and volume were calculated to evaluate PVS burden on 7 T magnetic resonance imaging images. We compared PVS burden between PD and HC, and conducted partial correlation analysis between PVS burden and clinical and imaging features. PD patients had a significantly more serious PVS burden in BG and midbrain, and the PVS number in BG was significantly correlated to the PD disease severity and L-dopa equivalent dosage. The fractional anisotropy and mean diffusivity values of certain subcortical nuclei and white matter fibers within or nearby the BG and midbrain were significantly correlated with the ipsilateral PVS burden indexes. Regarding to the midbrain, the difference between bilateral PVS burden was, respectively, correlated to the difference between fiber counts of white fiber tract passing through bilateral substantia nigra in PD. Our study suggests that PVS burden indexes in BG are candidate biomarkers to evaluate PD motor symptom severity and aid in predicting medication dosage. And our findings also highlight the potential correlations between PVS burden and both grey and white matter microstructures.